Mazhar Mughal
email: mazharmughal@free.fr

Charlotte Fontan Sers
email: charlotte.sers@esc-pau.fr

Cereal Production, Undernourishment and Food Insecurity in South Asia

Keywords: cereal production, undernourishment, food security, South Asia JEL Codes : O11, O13, 053, Q18

South Asia remains one of the major strongholds of hunger in the world, despite the fact that, following the Green Revolution, cereal production in the countries of this region tripled during the second half of the 20th century. This study examines the role played by this increase in cereal production in improving the region's nutrition and food security situation.

We study the association between the different aspects of food security and cereal production in South Asia that have prevailed over the past 25 years. We find a beneficial role of the production and yield of cereals in lowering the extent of undernourishment. A 1% increase in cereal production and yield is associated with upto 0.84% decrease in the prevalence of undernourishment. The impact is significant over a period of three years. The positive effect is particularly evident in the case of rice and maize production. An improvement is seen in the aspects of availability, stability and utilisation of food security but not in the aspect of access. These findings are robust to alternative specifications and techniques. The results explain, in part, the means by which South Asian nations have managed to stall relative increases in extreme hunger and food insecurity.

Introduction

In November 2019, the Government of Pakistan decided to immediately release an additional sum of Rs.6 billion (about US$38 million) to Utility Stores Corporation, the state-run grocery outlet 1 . The step was taken in order to provide subsidized food items for the poor households suffering from a seasonal spike in cereal and vegetable prices.

Combatting food insecurity has long been a major concern of governments across South Asia.

Poverty alleviation measures include delivery of subsidized cereals through public distribution systems (as mentioned above), food stamps, mid-day meals for school children, food for work programmes and provision of nutritional supplements to mothers and children.

During the past twenty-five years measures such as these have helped reduce the proportion of malnourished and food insecure populations in all eight countries of the region (FAOSTAT, 2016). The Millennium Development Goal (MDG) of reducing poverty by half was also achieved in time (IFPRI, 2016). The proportion of undernourished in South Asia's total population fell significantly from 23.9% in the early 1990s to 14.9% for the 2016-2018 period (Table 1). While the prevalence has fallen in all the eight countries of the region, the reduction has been most spectacular in Bangladesh and Nepal: in the former, the proportion of undernourished in the country's population halved from 32.8% estimated in 1990-1992 to 14.7% in 2016-2018 while the decrease was even greater in the latter, from 22.8% to 8.7% of the population. Nevertheless and despite this progress in relative terms about 278.5 million inhabitants of the region (corresponding to 14.7% of the population) are still estimated as being unable to meet their dietary needs [START_REF] Fao | The State of Food Security and Nutrition in the World[END_REF]. India, the largest and most populous country of the region, alone, accounts for a quarter of the world's total food insecure population. One Indian in seven (194 million or 14.5%) remains food insecure and one in three children under five years of age manifests stunted growth.

Table 1. Undernourishment Trends in South Asia

Figure 1. Average dietary composition in South Asian countries in 2017

A major objective of the South Asian governments' food security policies over the years has been to achieve self-sufficiency in staple grains, mainly rice, wheat and maize [START_REF] Pingali | Agricultural diversification in Asia : opportunities and constraints[END_REF]. Cereals account for half to three-quarters of average caloric intake in the countries of 1 https://www.brecorder.com/2019/11/08/542733/govt-to-disburse-rs6bn-for-utility-stores-corporation-immediately/ the region (Figure 1). Throughout the past half century, considerable effort was made across the region to attain self-sufficiency in cereal production. Agricultural research centers focused on producing new high-yield varieties better suited to South Asia's soils and climate.

Subsidies were provided on agricultural inputs including seeds, fertilizers, machinery, irrigation and electricity for tube wells. Small farmers were provided with cash benefits and subsidized credit. Efforts were made to improve access to agricultural credit and to reduce its cost (FAO, 2014). Programmes for agricultural insurance in case of natural and climatic disasters were established and extended. Another governmental measure aimed at improving production and protecting farmers from sharp market price fluctuations has been the minimum support price of cereals fixed every year. Some policy measures especially targeted the region's large number of small-holders, helping them improve their yield through better access to quality seeds, farm markets, credit and information. Thanks to these policy measures, South Asia has, over the past years, managed to enhance its cereal production as well as its yield and productivity. Most countries have succeeded in raising cereal yield two or three-fold since the beginning of the Green Revolution in the 1960s, and India and Pakistan have become practically self-sufficient in cereal production. Today, India, Pakistan and Bangladesh are among the world's largest producers of rice, with India and Pakistan among the top rice exporters. India exported close to 13 million tons of cereals in 2017 while Pakistan exported about 3 million tons.

What has been the role of these attempts at food self-sufficiency in achieving food security?

Is strong focus on increasing cereal production a significant factor in driving the fall in undernutrition seen in South Asia? Which of the four pillars of food security (availability, access, utilization and stability) as defined by FAO (2009) are most relevant? Extant literature has analyzed the role played in determining food security by household factors such as farm size [START_REF] Aidoo | Determinants of household food security in the Sekyere-Afram Plains Districts of Ghana[END_REF][START_REF] Muche | Determinants of Household Food Security among Southwest Ethiopia Rural Households[END_REF], access to credit [START_REF] Gebre | Determinants of Food Insecurity among Households in Addis Ababa City, Ethiopia[END_REF], income [START_REF] Matchaya | Estimating effects of constraints on food security in Malawi : policy lessons from regression quantiles[END_REF], and education of the household head (Magana-Lemus et al., 2016). [START_REF] Smith | Who are the World's Food Insecure? New Evidence from the Food and Agriculture Organization's Food Insecurity Experience Scale[END_REF] report low levels of education, weak social networks, less social capital, low household income and unemployment to be the five characteristics associated with the largest increase in the likelihood of experiencing food insecurity around the world. [START_REF] Imai | Women's Empowerment and Prevalence of Stunted and Underweight Children in Rural India[END_REF] show that rural Indian children's nutritional status, as exhibited in their likelihood of being stunted or underweight, improves with women's education and empowerment. [START_REF] Rahman | Does Non-farm Income Affect Food Security? Evidence from India[END_REF] report that being engaged in a non-agricultural livelihood has a positive effect on the overall food expenditure of rural Indian households, especially on non-cereal items. [START_REF] Kuma | Cash Crops and Food Security: Evidence from Ethiopian Smallholder Coffee Producers[END_REF] find that income from coffee production is a significant determinant of the food security of smallholding Ethiopian farmers.

The role of factors such as population growth (Hall et al. 2017), conflict (Martin-Shields and[START_REF] Martin-Shields | Food security and conflict: Empirical challenges and future opportunities for research and policy making on food security and conflict[END_REF] and climate change [START_REF] Bocchiola | Impact of climate change on agricultural productivity and food security in the Himalayas: A case study in Nepal[END_REF]Fao, 2015;[START_REF] Kang | Climate change impacts on crop yield, crop water productivity and food securitya review[END_REF] has also been examined at the macroeconomic level with respect to cross-country food security.

Asian Development Bank (2013) report that an increase of 1% in food price leads to a 0.4% increase in the prevalence of undernourishment. [START_REF] Brinkman | High Food Prices and the Global Financial Crisis Have Reduced Access to Nutritious Food and Worsened Nutritional Status and Health[END_REF] show that household food security, as measured by dietary diversity, reduced by 5 percent in Nepal, 8 percent in the Niger, and 23 percent in Haiti due to increased food prices and the financial crisis of 2007-08. [START_REF] Soriano | How important is economic growth for reducing undernourishment in developing countries?[END_REF] affirm that it takes two years for income growth to improve the nutrition situation in a sample of 22 developing countries. The indirect impact of income growth on undernourishment through social investments accounts for 50% of its total impact. Fontan and Mughal (2019) find evidence of significant beneficial effects of public agricultural spending on nutrition and food security in Africa but only for those countries allocating greater proportions of their budgets to agriculture.

While some studies have examined the role of agricultural income and expenditure on food security, the contribution of increasing cereal production and yields to the enhancement of a country's food security has so far received less attention. In its September 2019 report, FAO mention that persistent conflict and unfavourable climatic conditions in countries such as Afghanistan, Bangladesh and Pakistan affect agricultural production (including that of staples) which in turn renders the population food insecure [START_REF] Fao | The State of Food Security and Nutrition in the World[END_REF]. In this study, we analyze the cereal productionfood security relationship in the context of South Asia by exploring macroeconomic data on the eight countries from South Asia for the period from 1991 to 2015. We examine both the aggregate cereal production as well as the production of the region's three principal staple crops: rice, wheat and maize. We study the relationship between production, nutrition and food security in both its temporal and spatial dimensions.

Our findings indicate the beneficial role of the aforementioned focus on improving the production and yield of cereals and thus on South Asia's overall nutrition and food security situation. A 1% increase in cereal production and yield is found to be associated with as much as a 0.84 percent lower incidence of under-nutrition. The result mainly applies to the rice production and not to that of wheat. We find that an increase in South Asia's cereal production improves the availability, stability and utilization dimensions of the region's food security, but has no significant effect on the access dimension. These findings have useful policy implications in a developing-country context.

The study is organized as follows: In Section 2, we briefly describe the food security and cereal production situation of South Asian countries. Section 3 introduces the data and estimated model as well as empirical methodology. Results are presented and discussed in Section 4 and robustness measures in Section 5. Finally we present our Conclusion and policy implications.

Food security and cereal production in South Asia

State of hunger and food insecurity

One in nine human beings (about 820 million) still suffers from hunger (FAO, IFAD, UNICEF, WFP and WHO, 2019). In South Asia, the numbers of undernourished have marginally declined since the 1990s (Table 1). India, which accounts for 70% of the region's hunger has seen a 36% drop in the prevalence of undernourishment in the past quarter of a century despite a 48% increase in population (FAOSTAT, 2019). While the numbers have fallen in the other countries of the region, the situation in Afghanistan, Bangladesh and Pakistan has been challenging [START_REF] Fao | The State of Food Security and Nutrition in the World[END_REF]. In Afghanistan, the undernourished population doubled from 3.8 million in 1990-1992 to 10.6 million in 2016-2018 whereas in Pakistan, the number soared from 28.7 million to 40 million during the same period. In Afghanistan, decades of war and internal strife, earthquakes and failed crops have meant that the majority of the population lacks both access to food and the means of obtaining food. Population growth rates that are among the highest in the world have exacerbated the problem. Bangladesh, which had made significant strides in tackling under-nutrition in the past decades, is struggling to adequately shelter the over a million Rohingya refugees fleeing conflict in Myanmar. Similarly, Pakistan has been hosting millions of Afghan refugees for nearly four decades. Floods in the upper parts of the country and drought in the arid South-West and South-East have affected the country's food security situation.

In South Asia, average per capita calorie consumption is low by world standards, ranging in 2017 from 2090 kilocalories a day in Afghanistan to 2673 in Nepal (FAOSTAT). Inhabitants of Bangladesh, Nepal and Sri Lanka mainly rely on rice for their caloric intake while wheat is the chief source of calories in Afghanistan and Pakistan. The population of India's northern and western states likewise depends on wheat whereas rice is the staple food in the southern and eastern states. In traditionally rice-consuming parts of the region such as Bangladesh, rising incomes coupled with urbanization are leading to higher demand for wheat-based products.

Given the high dependence on cereals for covering caloric requirements (Figure 1), national food security policies have mainly focused on improving availability and access to affordable staple food. These policy interventions target the pricing and supply mechanisms as well as providing direct financial support programmes. All the countries of the region maintain public distribution systems supplying cereals at below-market prices. For this purpose, cereals are procured domestically, at pre-defined support prices or imported in case of insufficient domestic production. These systems assume an indispensable role in food importing countries such as Afghanistan and Bangladesh during global price spikes like those seen in 2007-20082 . Bangladesh, India and Pakistan maintain large-scale public grain reserves to counter such contingencies. India's Targeted Public Distribution System (TPDS) aims at improving the food security situation of 800 million poor by providing ten kilos of subsidized food grains per family every month. However, these distribution systems involve large subsidies and constantly struggle to identify and target the poor. Their reach is partial at best and losses are high in the presence of poor storage and delivery mechanisms [START_REF] Iqbal | Food security in South Asia: strategies and programmes for regional collaboration[END_REF]. In addition to distribution programmes, several schemes aim at improving nutrition and food security, directly or indirectly, by providing the poor with access to food through initiatives such as Mid-day Meal Programme and the National Rural Employment Guarantee Scheme (India), the Ehsas Programme (Pakistan) and Samurdhi Food Stamp Programme (Sri Lanka). India's Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS) is the world's largest public works programme3 . It guarantees up to hundred days of unskilled manual work on public projects during the lean seasons, at the statutory minimum wage, to all rural households. This allows poor households to smooth their food consumption and thus avoid food insecurity. Pakistan's Ehsas programme is an allencompassing social protection programme with 115 policy actions involving cash and asset transfers, subsidized loans, healthcare insurance, food vouchers, vocational training and scholarships aimed at alleviating hunger, poverty and economic disparity4 .

In addition to these government initiatives, international development agencies and Non-Governmental Organizations also run food support programmes, across the region, in areas hit by natural calamities, conflict and poverty.

State of cereal production

In 2018, South Asia produced more than 448 million tons of cereals, or about 15% of the global production (FAOSTAT, 2019). The region's share in the world production is far below its proportion of the world population, despite the Green Revolution of the 1960s and subsequent years which led to sharp increases in the region's cereal output. South Asia's cereal production today is more than twice that of Africa. The latter must import nearly half of its cereal requirements (201 million tons) compared with 16 million tons in the case of South Asia (FAOSTAT, 2019). South Asia's cereal yield grew threefold from 1961 to 2018 (Table 2). In comparison, cereal yield in Africa, as a whole, almost doubled during the same period. Today, South Asia produces about twice as much per hectare (31,802 hectograms/hectare) as Africa does (16,433 hectograms/hectare). Bangladesh by far leads the way with a yield of 44,112 hectograms per hectare, almost three times the level of 1961.

However the country must still import large quantities of cereals, mainly wheat5 . In contrast, India and Pakistan, despite their low yields of 31,608 hectograms per hectare and 31,708 hectograms per hectare respectively, have managed to become self-sufficient in cereal production. These two countries achieved the highest growth in cereal yield of the region during the 1961 -2018 period, corresponding to 234% and 270% respectively.

Table 2. Evolution of cereal yield per hectare in South Asia (1961 -2018) Figure 2. Cereal production in South Asian countries (share of total crops)

The predominance of cereal production varies widely among the countries of the region (Figure 2). In four out of eight countries, cereals represent more than 70% of the total crop production, reaching as high as 91% in Afghanistan. However, in India, the Maldives and Sri Lanka cereals account for less than half the crop production. With the exception of Bangladesh, cereals amount to less than half the value of agricultural production in all the countries of South Asia. This is due to the significant production of high value crops such as cotton, sugarcane and spices. South Asia produced 394 million tons of sugarcane in 2017 (FAOSTAT, 2019). The production of rice and wheat, in comparison, was 238 million tons and 146 million tons respectively (Table 3). South Asia (1991-2017) (tons) 3. Model, data and methodology

Table 3. Evolution of rice, wheat and maize production in

Model and data

We empirically examine the relationship between undernourishment/food security and cereal production in South Asia. We consider a population to be food secure when all individuals, at all times, have physical and economic access to adequate, safe and nutritious food to meet their dietary needs. Although, as [START_REF] Hoddinott | Operationalizing Household Food Security in Development Projects: An Introduction[END_REF] put it "there exist approximately 200 definitions and 450 indicators of food security", the above definition has the merit of emphasizing the four aspects of food security as defined by FAO (2009), namely availability, access, stability and utilization.

Our parsimonious baseline model for undernourishment / food security can be given as:

Undernourishment_prevalence/food security i,t = f (lncereal_prod i,t, lngdp_per_capita i,t, popgrowth i,t, inflation i,t, gfce i,t, climatologicaldisaster i,t, terrorkilledmillion i,t, foodcrisis)

(1)

where 'i' represents the corresponding South Asian country and 't' the year of the observation.

Dependent variables:

We take the prevalence of undernourishment (PoU) in each country as our baseline indicator.

This This indicator is useful in measuring long-term trends of hunger but does not monitor progress in achieving SDG Target 2.2 which calls for eradicating all forms of malnutrition.

Moderate (or less severe) levels of food insecurity, defined as uncertain access to food of sufficient quality and/or quantity, but not so extreme that it causes insufficient dietary energy intake, can increase the risk of seemingly divergent forms of malnutrition (FAO, IFAD, UNICEF, WFP and WHO, 2019). People experiencing moderate food insecurity face uncertainties about their ability to obtain food, and have to compromise on the quality and/or quantity of the food they consume. We study the association of cereal production with the four aspects of food security:

Availability corresponds to the supply of a sufficient quantity of nutritious food to all individuals, and can be measured by the indicator 'dietary energy supply as a percentage of average dietary energy requirement'. This indicator helps measure whether food insecurity in the country is mainly due to insufficiency of the food supply or to inadequate means of distribution.

Access indicates the physical and economic capacity of all individuals to acquire a sufficient quantity of nutritious food, and can be proxied by FAO's domestic food price index. The index, first introduced in 1996, is a measure of the monthly change in international prices of a basket of 23 food commodities and a total of 73 price series (FAO, 2013). The base period is [2002][2003][2004].

Stability refers to a consistent supply of nutritious food through effective management of price shocks arising from local or international economic or weather fluctuations. This aspect of food security can be measured by using variability of net per capita food production. This indicator corresponds to the variability of the food net per capita production measured in constant 2004-2006 international dollars (3-year average). It compares the variations of the per capita food production across countries and time.

Finally, utilization reflects the biological capacity of individuals to absorb nutritious food so that all the human body's physiological needs are met. This aspect underscores the importance of non-food inputs in food security, highlighted in the 1996 World Food Summit and could be proxied by health and sanitation indicators. We employ two alternate variables as proxy for individual food absorption capacity, namely the percentage of population using improved sanitation facilities and the mortality rate of under five children. The former points to the overall sanitary environment and living conditions in the country, whereas the latter reflects the prevalence of life-threatening diseases in the country.

Variables of interest:

Three variables of interest: the quantity, per capita production and cereal yield, all taken in logs, are alternately included in the model. We also consider South Asia's three main cereals (rice, wheat and maize). As discussed earlier, rice and wheat are the region's main staple crops. Maize is also cultivated throughout the region, particularly on less-productive land, and serves as a source of animal feed in addition to human consumption.

We assess the role of the diversity of nutritious food available to the consumers in driving food security by including the share of dietary energy derived from cereals, roots and tubers as an explanatory variable. Previous studies have already demonstrated a link between diversity of food supply and food security (see [START_REF] Arimond | Dietary diversity is associated with child nutritional status: evidence from 11 demographic and health surveys[END_REF][START_REF] Dillon | Agricultural Production, Dietary Diversity and Climate Variability[END_REF][START_REF] Hoddinott | Dietary Diversity as a Food Security Indicator[END_REF][START_REF] Kumar | If They Grow It, Will They Eat and Grow? Evidence from Zambia on Agricultural Diversity and Child Undernutrition[END_REF][START_REF] Ruel | Is dietary diversity an indicator of food security or dietary quality? A review of measurement issues and research needs[END_REF].

Controls:

We control for a number of economic, demographic, political and natural factors that are reported in the literature to be significant drivers of hunger and food insecurity. Economic development is deemed a key factor in decreasing hunger in developing countries (FAO, IFAD, WFP, 2015;FAO, 2015;[START_REF] Fontan Sers | From Maputo to Malabo: public agricultural spending and food security in Africa[END_REF]. Rising economic tide lifts the levels of food consumption and hence alleviates food insecurity as long as this growth is pro-poor. South Asia is one of the world's fastest growing regions with an average growth of 6.7% in 2018 (World Bank, 2019). GDP per capita is taken as the indicator of economic development.

Another relevant factor is population growth. Confronted with limited resources and economic opportunities, any rapid increase in population can impede efforts to reduce hunger.

It is important to include inflation in the model. Rising prices affect the poor proportionally more and could hit their food purchasing power particularly hard. Consequently, inflation, especially food price inflation has an adverse effect on food security (Cathie [START_REF] Herrmann | The Southern African customs union, cereal price policy in South Africa, and food security in Botswana[END_REF][START_REF] Kalkuhl | Food price volatility and its implications for food security and policy[END_REF].

Government plays a crucial role in determining a country's nutrition and food security situation through public spending on agriculture, tackling hunger and alleviating poverty [START_REF] Cuesta | Food security and public agricultural spending in Bolivia: Putting money where your mouth is?[END_REF]Magana-Lemus et al., 2016 ;[START_REF] Muche | Determinants of Household Food Security among Southwest Ethiopia Rural Households[END_REF][START_REF] Zakari | 2019 Table 3. Evolution of rice, wheat and maize production in South Asia-1991 -2017 (tons)[END_REF].

Countries with a low public agricultural expenditure per worker are found to have higher incidence of hunger (FAO, 2012 p. 6). We include government spending as a share of GDP to proxy government involvement in the economy.

Meteorological shocks such as cyclones, floods or drought resulting from failure of seasonal rains could jeopardize availability or access to food. South Asia is one of the world regions most hit by climate-related catastrophes. Floods are a recurrent phenomenon across the whole region, particularly during the monsoon season that lasts from June to September. Occasional droughts have devastated considerable areas of Afghanistan, Pakistan, India and Bangladesh.

We include a binary variable to account for food shortage, crop failure and famine to gauge the influence of such disasters on food security.

Yet another factor is the role of terrorism. Conflict and violence hurt economic activity, destroy lives, damage assets and could thereby aggravate hunger. South Asia has long suffered from ethnic, religious, communal and political terrorist activity. Over 67,000 people are reported to have been killed in terrorist attacks in the region since 1990 (National Consortium for the Study of Terrorism and Responses to Terrorism, 2016). We take terrorism related casualties per million population as an indicator of terrorist activity in South Asia.

Finally, we include a dummy variable for the 2007-2008 food crises to account for the detrimental effect of the food price shock on hunger in the developing countries [START_REF] Brinkman | High Food Prices and the Global Financial Crisis Have Reduced Access to Nutritious Food and Worsened Nutritional Status and Health[END_REF].

Table 4 gives the definitions and sources of the variables included in the study while the summary statistics of these variables are given in Table 5. The dataset is an unbalanced panel pertaining to the 1991 -2015 period. While several indicators included in the model have relatively few missing observations, some, such as food price index, have high numbers of missing observations, particularly for Afghanistan. On average there are 17.7 observations per country in the baseline model against a possible maximum of 25.

Methodology

The estimation proceeds as follows. In the first step, we alternately study the relationship between undernourishment prevalence on the one hand and indicators pertaining to the production of cereals on the other. The three indicators account for the quantity of cereals produced, per capita production and per hectare yield. We also examine undernourishment's association with the production of rice, wheat and maize in South Asia. These estimations are carried out using Fixed-effects panel estimator. The Hausman Specification test invariably maintains a P-value of 0.00 indicating that use of fixed-effect rather than random-effect estimator is preferable.

In the second step, we consider cereal production's association with the four aspects of food security, namely availability, access, stability and utilization.

In the final step, we test the robustness of our estimates. First, we check if it is the diversity of food supply and not merely cereal production that influences undernourishment. Second, we take heterogeneity into account in by alternately excluding the two outliers in our dataset.

The Maldives are the smallest country of the region, with negligible cereal production. The country is the most prosperous among South Asian countries and is close to eliminating hunger. At the other extreme, India corresponds to 75% of the region's population and an even greater share of its output.

Third, we account for the possibility of time lags. To this end, we carry out the estimations on the one, two, three, four and five-year lagged values of cereal production instead of the variable in level used in the baseline model. Finally, we estimate the baseline model using alternative econometric techniques to consider the possible dynamic structure of the underlying model. We employ Arellano and Bond, System GMM and Dynamic Panel Data (DPD) estimators to tackle potential endogeneity and auto-correlation issues [START_REF] Arellano | Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations[END_REF][START_REF] Arellano | Another look at instrumental variable estimation of errorcomponent models[END_REF][START_REF] Blundell | Initial conditions and moment restrictions in dynamic panel-data models[END_REF]. The Arellano-Bond model is consistent when T is small. It not only uses the second lags of the dependent variable but also all available proceeding lags; it poses the difficulty however that lagged levels are often poor instruments for first differences, especially for variables that are close to a random walk [START_REF] Perez Truglia | Applied Econometrics using Stata[END_REF]. System GMM has the quality of good small-sample properties, allows for weakly exogenous regressors and takes account of the endogeneity of the lagged dependent variable but is not efficient for large T, small N panels such as ours (Roodman, 2009a). The Dynamic Panel Data technique is considered more efficient in that it tackles endogeneity problems of the regressors and incorporates fixed-effects [START_REF] Roodman | How to do xtabond2: An introduction to difference and system GMM in Stata[END_REF].

Findings

Table 6 shows results of various production-related specifications. The association of undernourishment prevalence with cereal production, per capita production and yield, and all the three production indicators is found to be statistically significant and strong (Columns 1 -3). The sign of the three coefficients is negative suggesting the existence of a negative relationship between PoU and cereal production. Marginal effects given at the bottom of the table show that a 1% increase in cereal production is associated with a 0.42% decrease in the proportion of undernourished; the decrease in the latter, 0.6% is even stronger in the case of a 1% increase in per capita production and 0.84% in the case of per hectare yield. Higher production of staples not only improves their timely availability, particularly in the rural areas, but also improves economic access for the large number of farmers in South Asia with small holdings. Crop yields for small land-holders in South Asia are often low by international standards, which leaves many of them food insecure (see for instance [START_REF] Ahmad | Impact of Farm Households' Adaptations to Climate Change on Food Security: Evidence from Different Agro-ecologies of Pakistan[END_REF]. Increase in per hectare production raises household income and enhances purchasing power.

Crop-wise estimates show a similarly strong result for rice production (Column 4). A 1% increase in rice production is found to be associated with a 0.32% fall in undernourishment.

Rice is the principal staple for most of the population in the region. The coefficient for wheat production is found to be insignificant (p-value = 0.17). This is possibly due to the fact that wheat is the primary staple in only two countries of the region and an increase in wheat production does not substantially change the region's overall nutrition situation.

We find that cereal production is among three main factors driving undernourishment rates;

population growth rate and government consumption expenditure as share of GDP are found to be the two other strong factors. All things considered, high population growth intuitively leads to high incidence of under-and mal-nutrition.

Although population growth across the region has dropped from the highs seen in the 1970s

and the 80s, it continues to present a barrier to actions aimed at lifting the region's population out of poverty and hunger. South Asia's population increased from 1.16 billion in 1991 to 1.81 billion in 2018 (World Bank, 2019). This increase corresponds to twice the population of the United States of America Higher public spending, in contrast, leads to a lower proportion of undernourished population. Government spending can influence hunger directly through food provision schemes, and through pricing, subsidy and distribution mechanisms, as well as indirectly through investment in physical infrastructure and human development targeting the poor.

With the exception of these variables, the coefficients of other explanatory variables are mostly found to be statistically insignificant.

Table 6. Undernourishment and cereal production -production indicators Table 7. Food security and cereal productionthe four dimensions

The results presented above are also borne out in the estimates of multiple dimensions of food security reported in Table 7. Cereal production significantly and beneficially influences the availability, stability and utilization aspects of food security. The adequacy of dietary energy supply substantially increases (Column 1), the variability of per capita food production falls (Column 3), and health indicators improve (Columns 4 and 5). A 1% increase in grain production is associated with about 0.09% improvement in the adequacy of dietary energy supply and a 0.86% decrease in the variability of domestic per capita production. These findings again highlight the strong link we observed earlier between higher grain production and the improvement in South Asia's nutritional situation. Increased domestic production also helps the public storage and distribution systems to better protect the population from fluctuations in grain prices in the international market. In addition, greater food availability and price stability ultimately lead to improving the biological capacity of nutrition absorbtion, reflected in better access to sanitation facilities and lower incidence of child mortality.

The financial access dimension represented by the Food Price Index variable (Column 2)

does not significantly correlate with cereal production (p-value = 0.475) . Thanks to strong cereal price subsidy policies and other safety nets in force across the region, shortfall in domestic grain production does not significantly increase local food prices, thereby dampening the adverse impact of cereal production on food access. This result highlights the relative success of South Asian governments' sustained food price monitory mechanisms in sheltering the population from strong negative price shocks resulting from crop failures and climate hazards.

At the same time, the result raises doubt over the pertinence of food price index as an indicator of food security's access dimension. The association of cereal production with both the prevalence of undernourishment and the three dimensions of food security points to a possible non-negligible improvement in access to food. First, the availability and access dimensions are inseparably linked (Pinstrup-Andersen, 2009). Second, access increases not only from additional household income but also as a result of protection from negative price shocks. Third, improvement in sanitation and health outcomes also results from enhanced financial access to food. This shows that dimensions of food security should, in principal, all react to positive change in cereal production.

All things considered, the evidence of a beneficial effect of cereal production in South Asia on the region's nutrition and food security situation seems to be substantial.

Robustness Measures

We carry out a number of estimations to check for the robustness of our findings.

First, we explore the possibility that the drop in under-nutrition rates is a consequence of an increasingly diversified diet, more so than mere additional production of staples. Our evidence contradicts this possibility (Table 8, Column 1). We find that the share of cereals in South Asia's average caloric intake does not appear to influence the proportion of undernourished population in the region. South Asia's poor derive a very high share of their calorie requirement from cereal grains. Improved availability of staples seems to help them significantly whereas access to other sources of calorie does not appear to change the hunger situation. Food security in South Asia therefore responds more to the production of cereals than to their share in daily nutritional intake. This insignificant relationship between undernutrition and production diversity corroborates the findings of [START_REF] Sibhatu | Production diversity and dietary diversity in smallholder farm households[END_REF] in the context of Ethiopia and Kenya.

Second, we test whether our findings are sensitive to the presence of outliers in our dataset.

As discussed in Section 3.2, the Maldives and India represent two major outliers in the region, being at opposite ends of the spectrum in terms of area, population and agricultural production. The alternate exclusion of these two (Columns 2 -3) does not affect the negative relationship between undernourishment and cereal production found in the baseline estimations.

Third, we explore the possibility of a lagged effect of cereal production. As with estimation at levels, the significant negative association persists when one, two and three-year lags of cereal production are employed. However, the significance of the association dissipates beyond three lags.

Table 8. Undernourishment and cereal production -Alternative estimates Table 9. Undernourishment and cereal production -Dynamic model estimates Finally, we consider the dynamic structure underlying our baseline specification by estimating three models, System GMM, Arellano and Bond and Linear DPD. The results of these estimations corroborate our main finding of a significant salutary effect of cereal production on undernourishment in South Asia (Table 9). The association between cereal production and under-nutrition prevalence remains negative and statistically significant at the 1% level regardless of the technique employed. A 1% increase in cereal production, according to the System GMM estimate, corresponds to a 0.024% fall in undernourishment rates. The corresponding decrease in hunger, according to the Arellano and Bond and Linear DPD models is 0.132% and 0.373%. These estimated effects are somewhat smaller than those found with fixed-effect models, suggesting that the baseline model results might be biased upwards.

Conclusion

The United Nations declared the 2016 to 2025 period Decade of Action on Nutrition. In particular focus in this regard are the countries of Sub-Saharan Africa and South Asia, two regions where a significant proportion of the population still face hunger. South Asia alone is home to a third of the world's undernourished (FAO, IFAD, WFP, UNICEF, WHO, 2019).

Despite strong economic growth over the past quarter of a century that brought millions out of poverty, many in this region still lack sufficient food to satisfy dietary energy requirements. One of the objectives of South Asian countries' food policies over these decades has been to attain self-sufficiency in cereal production. Thanks to strong agricultural performance since the Green Revolution, production of wheat, rice and other cereal crops has doubled or tripled across the region. Nonetheless, the production of most of the countries in the region continues to fall short of the needs of a rapidly rising population, leaving the countries exposed to global price shocks. The need for self-sufficiency in staple grains was acutely felt during the food price hike of [START_REF] Ray | Changes in Food Consumption and the Implications for Food Security and Undernourishment: India in the 1990s[END_REF]-2008[START_REF] Pingali | Agricultural policy and nutrition outcomesgetting beyond the preoccupation with staple grains[END_REF]. In this study, we examined the role cereal production plays in driving South Asia's nutrition and food security situation. We found that higher production and better yield are associated with a lower proportion of undernourished population. This is particularly the case with rice, the main source of calories for much of South Asia's population. In rural areas, farmers retain part of their cereal production for home consumption. Similarly, landless labourers working in the fields are, in part, paid in grains. Increased cereal production is beneficial even in urban areas due to the subsidized supply of domestic food production.

Our findings suggest a positive effect of policies aimed at enhancing cereal production in South Asia. Governments should consequently step up efforts to improve crop yields which still lag far behind the levels achieved in the developed countries. Focusing on developing drought-resistant crop varieties, providing farmers with better quality seeds, information and technology, managing water distribution more efficiently and reducing post-harvest grain losses can all be pertinent policy steps in this direction.

Climate change is a looming challenge and South Asia is one of the regions hardest hit. The frequency of floods, droughts and extreme temperatures is increasing and farmers are already having to change their sowing practises to minimize crop loss [START_REF] Aryal | Climate change and agriculture in South Asia: adaptation options in smallholder production systems[END_REF]. The region is at risk of becoming the world's principal concentration of food insecure people by the middle of this century and the region's cereal production is feared to drop by 30% by the end of this century (IPCC, 2014).

Finally, combatting hunger in the region should not be at the cost of neglecting malnutrition.

Large numbers of South Asia's inhabitants are deficient in proteins and micronutrient deficiency is rife among children and women. Work on enhancing dietary quality and diversity should therefore go hand in hand with measures to increase quantity.

Figures and Tables:

Figure 1 .Figure 2 :

 12 Figure 1. Average dietary composition in South Asian countries (2017)

  indicator relates to the second Sustainable Development Goal (SDG). Objective 2.1 of the SDGs calls for ending hunger by 2030 and ensuring access by all the people, in particular the poor and people in vulnerable situations, including infants, to safe, nutritious and healthy, active life, and is computed by comparing the distribution of average, daily dietary energy consumption in a country's population with the distribution of dietary energy needs derived from the composition of the population by age, gender and physical activity levels.

	sufficient food all year round (United Nations, 2015). Prevalence of under-nutrition is the
	indicator commonly used in the literature to monitor severe or chronic food security (see for
	instance FAO, 2017; FAO, 2019; Martin-Shields and Stojetz, 2019; Ray, 2007). It is

computed from aggregated country-level data on food available for human consumption, compiled annually for most countries in the world in FAO's Food Balance Sheets

[START_REF] Fao | The State of Food Security and Nutrition in the World[END_REF]

. The indicator estimates the proportion of the population that lacks enough dietary energy for a

Table 4 . Variable definitions and sources Table 5. Summary statistics

 4

Table 1 : Undernourishment Trends in South Asia Number of Undernourished Undernourishment Prevalence 1990-1992 2016-2018 1990-1992 2016-2018

 1

	South Asia	291.2	277.7	23.90%	14.90%
	Afghanistan	3.8	10.6	29.50%	29.80%
	Bangladesh	36	24.2	32.80%	14.70%
	India	210.1	194.4	23.70%	14.50%
	Maldives	< 0.1	< 0.1	12.20%	10.30%
	Nepal	4.2	2.5	22.80%	8.70%
	Pakistan	28.7	40	25.10%	20,3%
	Sri Lanka	5.4	1.9	9%	22%
	Source: FAOSTAT, 2019

Table 2 . Evolution of cereal yields in South Asia (Hg/HA) -1961 -2017 Table 4. Variable definitions and sources Variables Definition Source

 2

	Undernutrition		Prevalence of undernourishment (%) (3-year average)	World Bank World Development Indicators database
	Lncereal_prod		Production of cereals in log	FAOSTAT
	lnperCapitaCerealProd		Production of cereals per capita in log	FAOSTAT
	Lncereal_yield		Yield of cereals in log	FAOSTAT
	ln rice			Production of tons of rice in log	FAOSTAT
	ln wheat			Production of tons of wheat in log	FAOSTAT
	ln maize			Production of tons of maize in log	FAOSTAT
	Foodsupplydiversity		Share of dietary energy derived from cereals, roots and tubes	FAOSTAT
	Average	Dietary	Energy
	Supply Adequacy		Dietary Energy Supply as a percentage of Average Dietary Energy Requirement	FAOSTAT
	Food Price Index		Domestic food price index	FAOSTAT
	Per capita food production
	variability			Variability of net per capita food production in constant 2004-2006 international dollars	FAOSTAT
	Improved sanitation facilities
	(% of population with access)	percentage of population using improved sanitation facilities	FAOSTAT
				United Nations Population Division.
	Mortality			Mortality rate, under-5 (per 1,000 live births)	World Population Prospects
	Lngdp_per_capita		GDP per capita in log	World Bank national accounts data
				United Nations Population Division.
	Popgrowth			Growth in total population	World Population Prospects
				International	Monetary	Fund,
				International Financial Statistics and
	Inflation			Inflation, consumer prices (annual %)	data files.
				World Bank World Development
	Gfce			Public spending to GDP ratio	Indicators database
	Climatologicaldisaster		dummy variable taking the value of 1 for the year of Climatological disaster (drought, earthquake, flood, extreme temperature event) associated with food shortage, crop failure or famine	Emergency Events Database (EM-DAT)
	terrorkilledmillion		terrorism related casualties per million population	Global Terrorism Database
	Food crisis			Dummy variable taking 1 for 2007-2008 and zero otherwise

Table 5 . Summary statistics

 5

	VARIABLES	N	mean St. Dev.	min	max
	Undernutrition	175 22.79	8.98	5.20	46.70
	Lncereal_prod	168 14.44	4.71	1.38	19.50
	Lnpercapitacerealprod	168 4.7222 1.8245 0.0178 5.8506
	Lncereal_yield	192 7.716	0.35	6.69	8.391
	Lnrice	168 15.13	2.41	10.53	18.89
	lnwheat	144 14.44	2.91	8.341	18.37
	lnmaize	191 11.89	3.74	0.69	16.98
	foodsupplydiversity	140 64.14	13.24	41	85
	Average Dietary Energy Supply Adequacy	175 106.7	7.90	89	131
	Food Price Index	104 6.280	2.02	2.66	9.50
	Per capita food production variability.	184 6.274	6.39	0.90	35.10
	Improved sanitation facilities (% of population with access) 192 46.34	24.66	6.20	98
	Mortality	200 74.54	41.20	8.60	174.20
	Lngdp_per_capita	171 6.593	0.75	5.45	8.56
	Popgrowth	198 1.961	1.32	-1.76	9.41
	Inflation	186 7.281	4.92	-18.10 30.55
	Gfce	164 11.642	4.58	4.13	22.93
	terrorkilledmillion	200 6.9943	19.99	0 170.61

Table 6 . Undernourishment and cereal production (Fixed-effect estimates)

 6 Note: Columns 1 to 6 show estimations with logs of cereal production, per capita cereal production, cereal yield, and production in log of rice, wheat and maize alternately included as variables of interest. Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

		(1)	(2)	(3)	(4)	(5)	(6)
		undernutrit	undernutrit	undernutrit	undernutrit	undernutrit	undernutrit
	VARIABLES	ion	ion	ion	ion	ion	ion
	Lncereal_prod	-11.73***
		(2.857)
	Lnpercapitacereal
	prod		-16.3797***
			(3.1609)
	Lncereal_yield			-21.53***
				(3.746)
	lnrice				-9.313***
					(2.261)
	lnwheat					-2.588
						(1.869)
	lnmaize						-2.159***
							(0.212)
	Lngdp_per_capit
	a	-1.116	-2.8634	1.918	-3.407*	-3.305**	-2.001
		(2.104)	(1.8216)	(2.223)	(1.915)	(1.306)	(1.327)
	popgrowth	4.150***	5.8926***	2.136***	3.044***	3.770***	2.716***
		(1.136)	(0.9570)	(0.722)	(0.735)	(0.798)	(0.560)
	inflation	-0.0839	-0.0844	-0.0994	-0.0642	-0.0162	0.0465

Table 7 . Food security and cereal production

 7 Notes: Columns 1 to 5 show estimations with Average Dietary Energy Supply Adequacy, Food Price Index, Per capita food production variability, Improved sanitation facilities and mortality as dependent variables respectively. Inflation is excluded from the list of explanatory variables when regressing food price index. Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

		(1)	(2)	(3)	(4)	(5)
		Average Dietary Energy Supply Adequacy	Food Price Index	Per capita food production variability.	Improved with access) sanitation facilities (% of population	Mortality
	VARIABLES
	Lncereal_prod	9.068***	-0.197	-11.39***	12.52***	-27.81***
		(2.627)	(0.274)	(2.647)	(3.302)	(6.352)
	Lngdp_per_capita	-2.713	0.444	12.38***	24.14***	-72.62***
		(1.935)	(0.298)	(1.841)	(2.296)	(4.417)
	popgrowth	-4.495***	-0.321**	0.852	-1.026	2.863**
		(1.045)	(0.150)	(0.563)	(0.702)	(1.351)
	inflation	0.104*		-0.194**	-0.0967	0.384**
		(0.0613)		(0.0756)	(0.0943)	(0.181)
	gfce	1.891***	0.136***	0.136	0.0463	-1.873***
		(0.237)	(0.0324)	(0.267)	(0.333)	(0.641)
	climatologicaldisaster -0.876	-0.00633	-0.731	0.105	1.609
		(0.537)	(0.0650)	(0.760)	(0.948)	(1.823)
	terrorkilledmillion	-0.0406*	0.00973	-0.0270	-0.0371	0.143*
		(0.0211)	(0.00666) (0.0323)	(0.0403)	(0.0776)
	foodcrisis	-0.604	-0.0408	2.750**	1.300	-3.830
		(0.846)	(0.0825)	(1.146)	(1.430)	(2.751)
	Constant	-37.26	5.460	105.9***	-313.9***	1,002***
		(41.08)	(3.885)	(35.57)	(44.37)	(85.36)

Table 8 . Undernourishment and cereal production -Alternative estimates

 8 Note: Column 1 shows estimation including food supply diversity as explanatory variable. Columns 2 and 3 show estimations using the dataset excluding Maldives and India respectively. Columns 4 shows estimation with one lag of the log of cereal production taken as the variable of interest. Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

		(1)	(2)	(3)	(4)
	VARIABLES	undernutrition undernutrition undernutrition undernutrition
	foodsupplydiversity	-0.432
		(0.360)
	lncereals		-12.96***	-7.634*
			(3.103)	(4.268)
	L.lncereal_prod				-7.156**
					(2.881)
	Lngdp_per_capita	-10.35***	-0.916	-9.043	-3.283
		(3.206)	(2.161)	(5.992)	(2.183)
	popgrowth	3.817***	3.830***	2.891*	4.612***
		(0.909)	(1.176)	(1.583)	(1.298)
	inflation	-0.0150	-0.0822	-0.0699	0.00418
		(0.0759)	(0.0680)	(0.0833)	(0.0730)
	gfce	-0.413	-1.477***	-1.266***	-1.434***
		(0.279)	(0.262)	(0.332)	(0.290)
	climatologicaldisaster	0.346	0.312	0.633	0.652
		(0.710)	(0.605)	(0.706)	(0.635)
	terrorkilledmillion	-0.0283	0.0130	0.0237	0.00957
		(0.0325)	(0.0232)	(0.0268)	(0.0246)
	foodcrisis	0.307	0.470	0.160	0.277
		(1.130)	(0.930)	(1.202)	(0.987)
	Constant	115.3***	258.2***	206.0***	165.9***
		(38.71)	(50.13)	(50.11)	(46.37)
	Marginal effects	-1.173	-0.4553	-0.2928	-0.1614
	Observations	111	101	83	102
	R-squared	0.505	0.746	0.738	0.703
	Number of id	7	5	5	6

Table 9 . Undernourishment and cereal production -Dynamic model estimates

 9 Note:Colums 1 -3 respectively show results for the System GMM, Arellano and Bond and Linear DPD models. Standard errors in parentheses, , , *** p<0.01, ** p<0.05, * p<0.1.

		(1)	(2)	(3)
	VARIABLES	undernutrition	undernutrition	undernutrition
	lncereals	-0.850***	-4.049***	-10.00***
		(0.0807)	(0.580)	(1.559)
	L.undernutrition	0.912***	0.862***
		(0.0140)	(0.0188)
	lngdp_per_capita	1.394***	1.155***	-2.232*
		(0.214)	(0.424)	(1.247)
	popgrowth	0.600***	0.178	4.194***
		(0.181)	(0.239)	(0.573)
	inflation	0.00207	-0.0262*	-0.0283
		(0.0107)	(0.0135)	(0.0354)
	gfce	-0.177***	-0.329***	-1.754***
		(0.0307)	(0.0596)	(0.147)
	climatologicaldisaster	-0.0256	0.0405	0.674**
		(0.0998)	(0.116)	(0.311)
	terrorkilledmillion	0.0116***	0.0221***	0.0124
		(0.00314)	(0.00445)	(0.0113)
	foodcrisis	-0.594***	-0.377**	0.226
		(0.133)	(0.179)	(0.455)
	Constant	7.419***	65.59***	211.2***
		(2.334)	(9.348)	(23.11)
	Marginal effects	-0.024	-0.132	-0.373
	Observations	102	96	106
	Number of id	6	6	6

Between January 2007 and April 2008, the price of coarse rice in Bangladesh and wheat in Afghanistan nearly doubled(World Bank, 2010).

See for instance: https://pubs.iied.org/G04267/

See for instance: https://www.globalvillagespace.com/ehsaas-a-so-called-welfare-program/

Bangladesh produces about 1 million tons of wheat and has to import nearly

million tons (source: https://www.dhakatribune.com/bangladesh/agriculture/2019/07/29/wheat-demand-growing-fast-in-bangladesh ).

Acknowledgements:

This study benefited from discussions with the participants of the 31st conference of the Third World Association (ATM), 22 -24 May 2017, Brussels, Belgium, IRMAPE Research Seminar at Pau Business School, 30 March 2017, and SFER conference on Politiques agricoles et alimentaires: trajectoires et réformes, 20-21 June 2018, Supagro, Montpellier, France. We are thankful to Sandra McJannett for language proofreading.


Xavier Bost

Vincent Labatut

Georges Linarès

Serial Speakers: a Dataset of TV Series

Keywords: TV series, Multimedia retrieval, Speech processing Xavier Bost, Vincent Labatut, Georges Linarès

For over a decade, TV series have been drawing increasing interest, both from the audience and from various academic fields. But while most viewers are hooked on the continuous plots of TV serials, the few annotated datasets available to researchers focus on standalone episodes of classical TV series. We aim at filling this gap by providing the multimedia/speech processing communities with Serial Speakers, an annotated dataset of 161 episodes from three popular American TV serials: Breaking Bad, Game of Thrones and House of Cards. Serial Speakers is suitable both for investigating multimedia retrieval in realistic use case scenarios, and for addressing lower level speech related tasks in especially challenging conditions. We publicly release annotations for every speech turn (boundaries, speaker) and scene boundary, along with annotations for shot boundaries, recurring shots, and interacting speakers in a subset of episodes. Because of copyright restrictions, the textual content of the speech turns is encrypted in the public version of the dataset, but we provide the users with a simple online tool to recover the plain text from their own subtitle files.

Introduction

For over a decade now, TV series have been drawing increasing attention. In 2019, the final season of Game of Thrones, one of the most popular TV shows these past few years, has averaged 44.2 million viewers per episode; many TV series have huge communities of fans, resulting in numerous online crowdsourced resources, such as wikis 1 , dedicated forums 2 , and YouTube channels. Long dismissed as a minor genre by the critics, some recent TV series also received critical acclaim as a unique space of creativity, able to attract even renowned full-length movie directors, such as Jane Campion, David Fincher or Martin Scorsese. Nowadays, TV series have their own festivals 3 . For more than half of the people 4 we polled in the survey reproduced in [START_REF] Bost | A storytelling machine? Automatic video summarization: the case of TV series[END_REF], watching TV series is a daily occupation, as can be seen on Fig. 1a. Such a success is probably related to the cultural changes caused by modern media: high-speed internet connections led to unprecedented viewing opportunities. As shown on Fig. 1b, television is no longer the main channel used to watch "TV" series: most of the time, streaming and downloading services are preferred to television. Unlike television, streaming and downloading platforms give control to the user, not only over the contents he may want to watch, but also over the viewing frequency. As a consequence, the typical dozen of episodes a TV series season contains is often watched over a much shorter period of time than the usual two months it is being broadcast on television. As can be seen on Fig. 2a, for almost 80% of the people we polled, watching a TV series season (about 10 hours in average) never takes more than a few weeks. As a major consequence, TV series seasons, usually released once a year, are not watched in a continuous way.

For some types of TV series, discontinuous viewing is generally not a major issue. Classical TV series consist of selfcontained episodes, only related with one another by a few recurring protagonists. Similarly, anthologies contain standalone units, either episodes (e.g. The Twilight Zone) or seasons (e.g. True detective), but without recurring characters. However, for TV serials, discontinuous viewing is likely to be an issue: TV serials (e.g. Game of Thrones) are based on highly continuous plots, each episode and season being narratively related to the previous ones. Yet, as reported on Fig. 2b, TV serials turn out to be much more popular than classical TV series: nearly 2/3 of the people we polled prefer TV serials to the other types, and 1/4 are more inclined to a mix between the classical and serial genres, each episode developing its own plot but also contributing to a secondary, continuous story. As a consequence, viewers are likely to have forgotten to some extent the plot of TV serials when they are, at last, about to know what comes next: nearly 60% of the people we polled feel the need to remember the main events of the plot before viewing the new season of a TV serial. Such a situation, quite common, provides multimedia retrieval with remarkably realistic use cases.

A few works have been starting to explore multimedia retrieval for TV series. Nonetheless, most of these works focus either on classical TV series, or on standalone episodes of TV serials. Due to the lack of annotated data, very few of them address the challenges related to the narrative continuity of TV serials. We aim at filling this gap by providing the multimedia/speech processing research communities with Serial Speakers, an annotated dataset focusing on three American TV serials: Breaking Bad (seasons 1-5 / 5), Game of Thrones (seasons 1-8 / 8), House of Cards (seasons 1-2 / 6). Besides multimedia retrieval, the annotations we provide make our dataset suitable for lower level tasks in challenging conditions (Subsection 3.1.). In this paper, we first describe the few existing related datasets, before detail-

5 xkcd.com/657
ing the main features of our own Serial Speakers dataset; we finally describe the tools we make available to the users for reproducing the copyrighted material of the dataset.

Related Works

These past ten years, a few commercial TV series have been annotated for various research purposes, and some of these annotations have been publicly released. We review here most of the TV shows that were annotated, along with the corresponding types of annotations, whenever publicly available.

Seinfeld (1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998) is an American TV situational comedy (sitcom). [START_REF] Friedland | Using artistic markers and speaker identification for narrativetheme navigation of seinfeld episodes[END_REF] rely on acoustic events to design a navigation tool for browsing episodes publicly released during the ACM Multimedia 2009 Grand Challenge.

Buffy the Vampire Slayer (1997)(1998)(1999)(2000)(2001) is an American supernatural drama TV series. This show was mostly used for character naming [START_REF] Everingham | Hello! my name is... buffy"-automatic naming of characters in tv video[END_REF], face tracking and identification [START_REF] Bäuml | Semi-supervised learning with constraints for person identification in multimedia data[END_REF], person identification [START_REF] Bäuml | A time pooled track kernel for person identification[END_REF], [START_REF] Tapaswi | Improved Weak Labels using Contextual Cues for Person Identification in Videos[END_REF], story visualization [START_REF] Tapaswi | StoryGraphs: Visualizing Character Interactions as a Timeline[END_REF], and plot synopses alignment (Tapaswi et al., 2014a) 6 . Ally McBeal (1997-2002) is an American legal comedydrama TV series. The show was annotated for performing scene segmentation based on speaker diarization [START_REF] Ercolessi | Segmenting tv series into scenes using speaker diarization[END_REF] and speech recognition [START_REF] Bredin | Segmentation of tv shows into scenes using speaker diarization and speech recognition[END_REF], plot deinterlacing [START_REF] Ercolessi | Toward plot de-interlacing in tv series using scenes clustering[END_REF], and story visualization (Ercolessi et al., 2012a) 7 .

Malcom in the Middle (2000Middle ( -2006) ) is an American TV sitcom. Seven episodes were annotated for story deinterlacing [START_REF] Ercolessi | Toward plot de-interlacing in tv series using scenes clustering[END_REF] and visualization (Ercolessi et al., 2012a) purposes.

The Big Bang Theory (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019) is also an American TV sitcom. Six episodes were annotated for the same visual tasks as those performed on Buffy the Vampire Slayer: face tracking and identification [START_REF] Bäuml | Semi-supervised learning with constraints for person identification in multimedia data[END_REF], person identification [START_REF] Bäuml | A time pooled track kernel for person identification[END_REF], [START_REF] Tapaswi | Improved Weak Labels using Contextual Cues for Person Identification in Videos[END_REF], and story visualization [START_REF] Tapaswi | StoryGraphs: Visualizing Character Interactions as a Timeline[END_REF]. [START_REF] Tapaswi | Knock! Knock! Who is it?" Probabilistic Person Iden-tification in TV series[END_REF] dataset provides crowdsourced manual transcripts, subtitles, episode outlines and textual summaries.

As can be seen, many of these annotations target visionrelated tasks. Furthermore, little attention has been paid to TV serials and their continuous plots, usually spanning several seasons. Instead, standalone episodes of sitcoms are overrepresented. And finally, even when annotators focus on TV serials (Game of Thrones), the annotations are never provided for more than a single season. Similar to the computer vision ACCIO dataset for the series of Harry Potter movies [START_REF] Ghaleb | Accio: A Data Set for Face Track Retrieval in Movies Across Age[END_REF], our Serial Speakers dataset aims in contrast at providing annotations of several seasons of TV serials, in order to address both the realistic multimedia retrieval use cases we detailed in Section 1., and lower level speech processing tasks in unusual, challenging conditions.

Duration (# episodes) Show

BB

GOT HOC

Description of the Dataset

Our Serial Speakers dataset consists of 161 episodes from three popular TV serials:

Breaking Bad (denoted hereafter BB), released between 2008 and 2013, is categorized on Wikipedia as a crime drama, contemporary western and a black comedy. We annotated 62 episodes (seasons 1-5) out of 62.

Game of Thrones (GOT) has been introduced above in Section 2. We annotated 73 episodes (seasons 1-8) out of 73.

House of Cards (HOC) is a political drama, released between 2013 and 2018. We annotated 26 episodes (seasons 1-2) out of 73.

Overall, the total duration of the video recordings amounts to 135 hours (135:34:27). Table 2 details for every season of each of the three TV serials the duration of the video recordings, expressed in "HH:MM:SS", along with the corresponding number of episodes (in parentheses).

Speech Turns

As in any full-length movie, speech is ubiquitous in TV serials. As reported in Table 1, speech coverage in our dataset ranges from 35% to 46% of the video duration, depending on the TV series, for a total amount of about 51 hours. As can be seen, speech coverage is much more important (46%) in HOC than in BB and GOT (respectively 38% and 35%). As a political drama, HOC is definitely speech oriented, while the other two series also contain action scenes. Interestingly, speech coverage in GOT tends to decrease over the 8 seasons, especially from the fifth one.

The first seasons turn out to be relatively faithful to the book series they are based on, while the last ones tend to depart from the original novel. Moreover, with increasing financial means, GOT progressively moved to a pure fantasy drama, with more action scenes.

The basic speech units we consider in our dataset are speech turns, graphically signaled as sentences by ending punctuation signs. Unlike speaker turns, two consecutive speech turns may originate in the same speaker.

Boundaries. The boundaries (starting and ending points) of every speech turn are annotated. During the annotation process, speech turns were first based on raw subtitles, as retrieved by applying a standard OCR tool to the commercial DVDs. Nonetheless, subtitles do not always correspond to speech turns in a one-to-one way: long speech turns usually span several consecutive subtitles; conversely, a single subtitle may contain several speech turns, especially in case of fast speaker change. We then applied simple merging/splitting rules to recover the full speech turns from the subtitles, before refining their boundaries by using the forced alignment tool described in [START_REF] Mcauliffe | Montreal forced aligner: Trainable text-speech alignment using kaldi[END_REF]. The resulting boundaries were systematically inspected and As can be seen on Fig. 3a, the statistical distribution of the speech turns duration, here plotted on a log-log scale as a complementary cumulative distribution function, seems to exhibit a heavy tail in all three cases. This is confirmed more objectively by applying the statistical testing procedure proposed by [START_REF] Clauset | Power-law distributions in empirical data[END_REF], which shows these distributions follow power laws. This indicates that the distribution is dominated by very short segments, but that there is a non-negligible proportion of very long segments, too. It also reveals that the mean is not an appropriate statistic to describe this distribution.

Speakers. By definition, every speech turn is uttered by a single speaker. We manually annotated every speech turn with the name of the corresponding speaking character, as credited in the cast list of each TV series episode. A small fraction of the speech segments (BB: 1.6%, GOT: 3%, HOC: 2.2%) were left as unidentified ("unknown" speaker). In the rare cases of two partially overlapping speech turns, we decided to cut off the first one at the exact starting point of the second one to preserve as much as possible its purity.

Overall, as can be seen in Table 1, 288 speakers were identified in BB, 468 in GOT and 264 in HOC. With an average speaking time of 132 seconds by speaker, HOC contains more speakers than GOT (175 seconds/speaker), which in turn contains more speakers than BB (218 seconds/speaker). Fig. 3b shows the distribution of the speaking time (expressed in percentage of the total speech time) for all speakers, again plotted on a log-log scale as a complementary cumulative distribution function. Once again, the speaking time of each speaker seems to follow a heavy-tailed distribution, with a few ubiquitous speakers and lots of barely speaking characters. This is confirmed through the same procedure as before, which identifies three power laws. If we consider that speaking time captures the strength of social interactions (soliloquies aside), this is consistent with results previously published for other types of weighted social networks [START_REF] Li | Network connection strengths: Another power-law?[END_REF][START_REF] Barthélemy | Characterization and modeling of weighted networks[END_REF]. Nonetheless, as can be seen on the figure, the main speakers of GOT are not as ubiquitous as the major ones in the other two series: while the five main protagonists of BB and HOC respectively accumulate 64.3 and 48.6% of the total speech time, the five main characters of GOT "only" accumulate 25.6%. Indeed, GOT's plot, based on a choral novel, is split into multiple storylines, each centered on one major protagonist. Moreover, even major, recurring characters of TV serials are not always uniformly represented over time. Fig. 4 depicts the lower part of correlation matrices computed between the speakers involved in every season of BB (Fig. 4a) and GOT (Fig. 4b): the distribution of the relative speaking time of every speaker in each season is first computed, before the Pearson correlation coefficient is calculated between every pair of season distribution.

As can be seen, the situation is very contrasted, depending on the TV serial. Whereas the major speakers of BB remain quite the same over all five seasons (correlation coefficients close to 1, except for the very last, fifth one, with a few entering new characters), GOT exhibits quite lower correlation coefficients. For instance, the main speakers involved in the first season turn out to be quite different from the speakers involved in the other ones (average correlation coefficient with the other seasons only amounting to 0.56 ± 0.05). Indeed, GOT is known for numerous, shocking deaths of major characters 11 . Moreover, GOT's narrative usually focuses alternatively on each of its multiple storylines, but may postpone some of them for an unpredictable time, resulting in uneven speaker involvement over seasons. Fig. 6 depicts the relative speaking time in every season of the 12 most active speakers of GOT. As can be seen, some characters are barely present in some seasons, for instance, Jon (rank #4) in Season 2, or even absent, like Tywin (rank #12) in Seasons 5-8. Furthermore, as can be noticed on Fig. 6, the relative involvement of most of these 12 protagonists in Seasons 7-8 is much more important than in the other ones: indeed, Seasons 7-8 are centered on fewer speakers (respectively 66 and 50 vs. 124.3 ± 11.8 in average in the first six ones). Speaker annotations make our dataset suitable for the speaker diarization/recognition tasks, but in especially challenging conditions: first, and as stated in [START_REF] Bredin | Improving speaker diarization of tv series using talking-face detection and clustering[END_REF], the usual 2-second assumption made for the 11 See got.show, for an attempt to automatically predict the characters who are the most likely to die next. speech turns by most of the state-of-the-art speaker diarization systems does no longer stand. Second, the high number of speakers involved in TV serials, along with the way their utterances are distributed over time, make onestep approaches particularly difficult. In such conditions, multi-stage approaches should be more effective [START_REF] Tran | Comparing multi-stage approaches for crossshow speaker diarization[END_REF]. Besides, as noted in [START_REF] Bredin | Improving speaker diarization of tv series using talking-face detection and clustering[END_REF], the spontaneous nature of the interactions, the usual background music and sound effects heavily hurt the performance of standard speaker diarization/recognition systems [START_REF] Clément | Speaker diarization of heterogeneous web video files: A preliminary study[END_REF].

Textual content. Though not provided with the annotated dataset for obvious copyright reasons12 , the textual content of every speech turn has been revised, based on the output of the OCR tool we used to retrieve the subtitles. In particular, we restored a few missing words, mostly for BB, the subtitles sometimes containing some deletions. BB contains 229,004 tokens (word occurrences) and 10,152 types (unique words); GOT 317,840 tokens and 9,275 types; and HOC 153,846 tokens and 8,508 types. As the number of tokens vary dramatically from one TV serial to the other, we used the length-independent MTLD measure (McCarthy and Jarvis, 2010) to assess the lexical diversity of the three TV serials. With a value of 88.2 (threshold set to 0.72), the vocabulary in HOC turns out to be richer than in GOT (69.6) and BB (64.5). More speech oriented, HOC also turns out to exhibit more lexical diversity than the other two series.

Interacting Speakers

In a subset of episodes, the addressees of every speech turn have been annotated. Trivial within two-speaker sequences, such a task, even for annotators, turns out to be especially challenging in more complex conditions: most of the time, the addressees have to be inferred both from visual clues and from the semantic content of the interaction. In soliloquies (not rare in HOC), the addressee field was left empty. Not frequently addressed alone, the task of determining the interacting speakers is nonetheless a prerequisite for social network-based approaches of fiction work analysis, which generally lack annotated data to intrinsically assess the interactions they assume [START_REF] Labatut | Extraction and analysis of fictional character networks: A survey[END_REF]. Moreover, speaker diarization/recognition on the one hand, detection of interaction patterns on the other hand, could probably benefit from one another and be performed jointly.

As an example, Fig. 5 shows the conversational networks based on the annotated episodes for each serial. The vertex sizes match their degree, while their color corresponds to their betweenness centrality. This clearly highlights the obvious main characters such as Walter White (BB) or Francis Underwood (HOC); but also more secondary characters that have very specific roles narrative-wise, e.g. Jaime Lannister who acts as a bridge between two groups of characters corresponding to two distinct narrative arcs. This illustrates the interest of leveraging the social network of characters when dealing with narrative-related tasks.

Shot Boundaries

Besides speech oriented annotations, the Serial Speakers dataset contains a few visual annotations. For the first season of each of the three TV series, we manually annotated shot boundaries. A video shot, as stated in [START_REF] Koprinska | Temporal video segmentation: A survey[END_REF], is defined as an "unbroken sequence of frames taken from one camera". Transitions between video shots can be gradual (fade-in/fade-out), or abrupt ones (cuts). Most of the shot transitions in our dataset are simple cuts.

The first seasons of BB, GOT, and HOC respectively contain 4,416, 9,375 and 8,783 shots, with and average duration of 4.5, 3.4 and 4.4 seconds. Action scenes in GOT are likely to be responsible for shorter shots in average. Shot boundary detection is nowadays well performed, especially when consecutive shots are abruptly transitioning from one another. As a consequence, it is rarely addressed for itself, but as a preliminary task for more complex ones.

Recurring Shots

Shots rarely occur only once in edited video streams: in average, a shot occurs 10 times in BB, 15.2 in GOT and 17.7 in HOC. Most of the time, dialogue scenes are responsible for such shot recurrence. As can be seen on Fig. 8, within dialogue scenes, the camera typically alternates between the interacting characters, resulting in recurring, possibly alternating, shots. We manually annotated such recurring shots, based on similar framing, in the first season of the three TV series. As stated in [START_REF] Yeung | Segmentation of video by clustering and graph analysis[END_REF], recurring shots usually capture interactions between characters. Relatively easy to cluster automatically, recurring shots are especially useful to multimodal approaches of speaker diarization [START_REF] Bost | Audiovisual speaker diarization of tv series[END_REF]. Besides, recurring shots often result in complex interaction patterns, denoted logical story units in [START_REF] Hanjalic | Automated high-level movie segmentation for advanced video-retrieval systems[END_REF]. Such patterns are suitable for supporting local speaker diarization approaches [START_REF] Bost | Constrained speaker diarization of tv series based on visual patterns[END_REF], or for providing extractive summaries with consistent subsequences [START_REF] Bost | Remembering winter was coming[END_REF].

Scene Boundaries

Scenes are the longest units we annotated in our dataset.

As required by the rule of the three unities classically prescribed for dramas, a scene in a movie is defined as a homogeneous sequence of actions occurring at the same place, within a continuous period of time.

Though providing annotators with general guidelines, such a definition leaves space for interpretation, and some subjective choices still have to be made to annotate scene boundaries.

First, temporal discontinuity is not always obvious to address: temporal ellipses often correspond to new scenes, but sometimes, especially when short, they hardly break the narrative continuity of the scene.

Figure 9: Long shot opening a scene. Second, as shown on Fig. 9, scenes often open with long shots that show the place of the upcoming scene. Though there is no, strictly speaking, spatial continuity between the first shot and the following ones, they obviously belong to the same scene, and should be annotated as such.

Finally, action homogeneity may also be tricky to assess. For instance, a phone call within a scene may interrupt an ongoing dialogue, resulting in a new phone conversation with another character, and possibly in a new action unit. In such cases, we generally inserted a new scene to capture the interrupting event, but other conventions could have been followed. Indeed, the choice of scene granularity remains highly dependent on the use case the annotators have in mind for annotating such data: special attention to speaker interactions would for instance invite to introduce more frequent scene boundaries.

Overall, BB contains 1,337 scenes, with an average duration of 127.1 seconds; GOT 1,813 scenes (avg. duration of 132.6 seconds); HOC 1,048 scenes (avg. duration of 73.2 seconds). Once again, HOC contrasts with the two other series, with many short scenes. Fig. 7 shows the joint distribution of the number of speakers by scene and the duration of the scene. For visualization purposes, the joint distribution is plotted as a continuous bivariate function, as fitted by applying kernel density estimate.

As can be seen from the marginal distribution represented horizontally above each plot, the number of speakers in each scene remains quite low: 2 in average in BB, 2.1 in HOC, and a bit more (2.4) in GOT. Besides, the number of characters in each scene, except maybe in GOT, is not clearly correlated with its duration. Moreover, some short scenes surprisingly do not contain any speaking character: most of them correspond to the opening and closing sequences of each episode. Finally, the short scenes of HOC generally contain two speakers.

Table 3 provides an overview of the annotated parts of the Serial Speakers dataset, along with the corresponding types of annotations. In the table, "Speech turns" stand for the annotation of the speech turns (boundaries, speaker, text); "Scenes" for the annotation of the scene boundaries; "Shots" for the annotation of the recurring shots and shot boundaries; and "Interlocutors" for the annotation of the interacting speakers 13 .

Text Recovering Procedure

Due to copyright restrictions, the published annotation files do not reproduce the textual content of the speech turns. Instead, the textual content is encrypted in the public version of the Serial Speakers dataset, and we provide the users with a simple toolkit to recover the original text from their own subtitle files 14 . Indeed, the overlap between the textual content of our dataset and the subtitle files is likely to be large: compared to the annotated text, subtitles may contain either insertions (formatting tags, sound effect captions, mentions of speaking characters when not present onscreen), or some deletions (sentence compression), but very few substitutions. Every word in the transcript, if not deleted, generally has the exact same form in the subtitles. As a consequence, the original word sequence can be recovered from the subtitles. Our text recovering algorithm first encrypts the tokens found in the subtitle files provided by the user, before matching the resulting sequence with the original encrypted token sequence. The general procedure we detail below is likely to be of some help to annotators of other movie datasets with similar copyrighted material.

Text Encryption

For the encryption step, we used truncated hash functions because of the following desirable properties: deterministic, hash functions ensure that identical words are encrypted in the same way in the original text and in the subtitles; they do not reveal information about the original content, allowing the public version of our dataset to comply with the copyright restrictions; they are efficient enough to quickly process the thousands of word types contained in the subtitles; moreover, once truncated, hash functions result in collisions, able to prevent simple dictionary attacks. Indeed, the main requirement in our case is only to prevent collisions from occurring too close from each other: even if two different words were encrypted in the same way, they 13 The annotation files are available online at: doi.org/10.6084/m9.figshare.3471839 14 The toolkit is available online at: github.com/bostxavier/Serial-Speakers would unlikely be close enough to result in ambiguous subsequences.

In the public version of our dataset, we compute the first three digits of the SHA-256 hash function of all of the tokens (including punctuation signs) and the exact same encryption scheme is applied to the subtitle files, as provided by the users, resulting in two encrypted token sequences for every episode of the three TV series.

Subtitle Alignment

We then apply to the two encrypted token sequences the Python Difflib sequence matching algorithm 15 , built upon the approach detailed in [START_REF] Ratcliff | Patternmatching-the gestalt approach[END_REF]. Once aligned with the encrypted subtitle sequence, the tokens of the dataset are decryted by retrieving from the subtitles the original words. The whole text recovering procedure is summarized on Fig. 10. The annotated dataset with clear text, materialized by the gray box (Box 1) on the figure, is not publicly available. Instead, in the public annotations, the text is encrypted (Box 2). In order to recover the text, the user has to provide h(is/er) own subtitle files (Box 3), which are encrypted by our tool in the same way as the original dataset text (Box 4); the resulting encrypted token sequence is matched with the corresponding token sequence of speech turns (red frame on the figure), before the text of the speech turns is recovered from the subtitle words (Box 5).

Experiments and Results

In order to assess the text recovering procedure, we automatically recovered the textual content from external, publicly available subtitle files, and compared it to the annotated text. Table 4 reports in percentage for each of the three series the average error rates by episode, both computed at 15 docs.python.org/3/library/difflib.html the word level (word error rate, denoted WER in the table) and at the sentence level (sentence error rate, denoted SER). In addition, we reported for every episode the average number of reference tokens (denoted # tokens), and the average number of insertions, deletions, and substitutions in the reference word sequence (respectively denoted Ins, Del, Sub). Because of possibly inconsistent punctuation conventions between the annotated and subtitle text, we systematically removed the punctuation signs from both sequences before computing the error rates. As can be seen, the average error rates remain remarkably low: the word error rate amounts to less than 1% in average. The sentence error rate also remains quite low: about 1% for GOT and HOC, and a bit higher (4.6%) for BB. As can be seen in the right part of the table, deletions are responsible for most of the errors, especially in BB: as noted in Subsection 3.1., we restored the words missing in the subtitles when annotating the textual content of the speech turns. Such missing words turn out to be relatively frequent in BB, which can in part explain the higher number of deletions ( 53 deleted words in average out of 3,700). Moreover, truncating the hash function to the first three digits does not hurt the performance of the text recovering procedure, while preventing simple dictionary attacks: the exact same error rates (not reported in the table) are obtained when keeping the full hash (64 hexadecimal digits). In order to allow the user to quickly inspect and edit the differences between the annotated text and the subtitles, our tool inserts in the recovered dataset an empty tag <> at the location of deleted reference tokens. Similarly, we signal every substituted token with an enclosing tag (e.g. <Why>). As will be seen when using the toolkit, most of the differences come from different punctuation/quotation conventions between the annotation and subtitle files, and rarely impact the vocabulary or the semantics. The whole recovering process turns out to be fast: 8.3 seconds for GOT (73 episodes) on a personal laptop (Intel Xeon-E3-v5 CPU); 6.73 for BB (62 episodes); 4.41 for HOC (26 episodes). We tried to keep the toolkit as simple as possible, with a single text recovering Python script with few dependencies.

Conclusion and Perspectives

In this work, we described Serial Speakers, a dataset of 161 annotated episodes from three popular TV serials, Breaking Bad (62 annotated episodes), Game of Thrones (73), and House of Cards (26). Serial Speakers is suitable for addressing both high level multimedia retrieval tasks in real world scenarios, and lower level speech processing tasks in challenging conditions. The boundaries, speaker and textual content of every speech turn, along with all scene boundaries, have been manually annotated for the whole set of episodes; the shot boundaries and recurring shots for the first season of each of the three series; and the interacting speakers for a subset of 10 episodes. We also detailed the simple text recovering tool we made available to the users, potentially helpful to annotators of other datasets facing similar copyright issues. As future work, we will first consider including the face tracks/identities provided for the first season of GOT in (Tapaswi et al., 2015a), but these face tracks, automatically generated, would need manual checking before publication. Furthermore, we plan to investigate more flexible text encryption schemes: due to the uniqueness property, hash functions, even truncated, are not tolerant to spelling/OCR errors in the subtitles. Though the correct word is generally recovered from the surrounding tokens, it would be worth investigating encryption functions that would preserve the similarity between simple variations of the same token.

Figure 1 :

 1 Figure 1: TV series, viewing conditions.

Figure 2 :

 2 Figure 2: TV series, season viewing time; favorite genre.

Figure 3 :

 3 Figure 3: Speech turns duration and speaking time/speaker.

Figure 4 :

 4 Figure 4: Speakers correlation across seasons.

Figure 5 :

 5 Figure 5: Conversational networks extracted from the annotated episodes. Vertex size and color represent degree and betweenness, respectively.

Figure 6 :

 6 Figure 6: Relative speaking time over every season of the top-12 speakers of GOT.

Figure 7 :

 7 Figure 7: # speakers/scene vs. scene duration.

Figure 8 :

 8 Figure 8: Example of two alternating recurring shots.

Figure 10 :

 10 Figure 10: Text recovering procedure.

Table 1 :

 1 Speech features.

	also focus on speaker identification and pro-
	vide audiovisual annotations for these six episodes 8 . In ad-
	dition to these audiovisual annotations, Roy et al. (2014)
	publish in the TVD dataset other crowdsourced, linguisti-
	cally oriented resources, such as manual transcripts, subti-
	tles, episode outlines and textual summaries 9 .
	Game of Thrones (2011-2019) is an American fantasy
	drama. Tapaswi et al. (2014b) make use of annotated face
	tracks and face identities in the first season (10 episodes).
	In addition, Tapaswi et al. (2015a) provide the ground truth
	alignment between the first season of the TV series and the
	books it is based on 10 . For a subset of episodes, the TVD

Table 2 :

 2 Duration of the video recordings.

	Season
	1	05:32:44 (7) 08:58:28 (10) 10:48:15 (13)
	2	09:51:08 (13) 08:41:56 (10) 10:37:10 (13)
	3	09:49:40 (13) 08:52:04 (10)	( )
	4	09:46:16 (13) 08:41:05 (10)	( )
	5	12:15:36 (16) 08:56:50 (10)	( )
	6	( ) 08:55:43 (10)	( )
	7	( )	06:58:54 (7)	( )
	8	( )	06:48:31 (6)	( )
	Total	47:15:26 (62) 66:53:34 (73) 21:25:26 (26)

  manually adjusted whenever necessary. Such annotations make our dataset suitable for the speech/voice activity detection task. Overall, as reported in Table1, the dataset contains 109,366 speech turns. Speech turns are relatively short: the median speech turn duration amounts to 1.3 seconds for GOT, 1.2 for HOC, and only 1.1 for BB.

Table 3 :

 3 Annotation overview.

		Speech turns-Scenes		Shots			Interlocutors
	Show	BB	GOT	HOC	BB	GOT	HOC	BB	GOT	HOC
	Season
	1							4, 6 3, 7, 8 1, 7, 11
	2							3, 4
	3
	4
	5
	6
	7
	8

Table 4 :

 4

		WER	SER	# tokens Ins	Del Sub
	Show
	BB	1.6	4.6	3699.8 0.2 53.1	4.1
	GOT	0.4	1.2	4353.2 0.1 13.8	1.9
	HOC	0.2	0.7	5918.0 0.1	7.4	2.3

Text recovering: avg. error rates (%) / episode.

Visual (face tracks and identities) and linguistic (video alignment with plot synopses) annotations of the fifth season can be found at cvhci.anthropomatik.kit.edu/mtapaswi/projectsmma.html

7 Annotations (scene/shot boundaries, speaker identity) of the first four episodes are available at herve.niderb.fr/data/ally

mcbeal 8 cvhci.anthropomatik.kit.edu/mtapaswi/

projectspersonid

.html 9 tvd.niderb.fr/ 10 cvhci.anthropomatik.kit.edu/mtapaswi/projectsbook align.html

Instead, we provide the users with online tools for recovering the textual content of the dataset from external subtitle files. See Section 4. for a description.

Acknowledgements

This work was partially supported by the Research Federation Agorantic FR 3621, Avignon University.

(b) GOT. Adam Galloway Barney Hull Bob Birch Brian Carly Heath Catherine Durant Charles Holburn Christina Gallagher Claire Underwood Diane Donald Blythe Douglas Stamper Drew Coughlin Edward Meechum Evelyn Baxter Felicity Holburn Francis Underwood Freddy Hayes Garrett Walker Gillian Cole Henry Chapman Jack Warton Janine Skorsky Jim Matthews Linda Vasquez Lucas Goodwin Maggie Wilson Michael Kern Nancy Kaufberger Nash Aarons Peter's daughter Peter Russo Rachel Posner Randy Flint Steve Jones Tom Hammerschmidt VP's Chief of Staff Walter Doyle Zoe Barnes


Célestin Matte

Marine Minier

Mathieu Cunche

Franck Rousseau

Privacy-preserving Wi-Fi tracking systems

Privacy-preserving Wi-Fi tracking systems

C élestin Matte [START_REF]CNIL's obligations[END_REF] , Marine Minier 1 , Mathieu Cunche 1 , Franck Rousseau 2 1 Universit é de Lyon, INRIA, INSA-Lyon, CITI-INRIA, France [START_REF] Demir | C édric Analysing the privacy policies of Wi-Fi trackers and statistics[END_REF] Grenoble Institute of Technology, CNRS Grenoble Informatics Laboratory UMR 5217, Grenoble, France

WI-FI TRACKING SYSTEMS

Wi-Fi-enabled smartphones frequently emit frames because they scan for access points Each frame contains a unique identifier of the device: the MAC address Wi-Fi tracking systems monitor and store these frames in order to make statistics: number of visitors frequency of visits travel paths etc.

PRIVACY ISSUES

Lot of private information stored -much more than needed to make basic statistics Anyone with access -legitimate or not -to that data can get a lot of information about passers-by In France, made illegal by the "Informatique et Libert é" law (LIL). The CNIL made precise recommandations for this case of information collecting so that one knows if they respect the law [1]:

Data must be deleted when the person exits the place Used algorithm must ensure a strong collision rate, i.e. an identifier must correspond to several people People must give their explicit consent it if one wants to store data for a longer period (opt-in system).

We can work on storing only information valuable for statistics

HASHING AND TRONCATION

Principle: Same as hashing, but only keep a small part of the result the less you keep, the more collisions you'll get Also possible to troncate before hashing, in order to manually increase collision rate (first 3 bytes of the MAC address are the constructor identifier) Problem: Still easy to reverse? BITMAPS Principle: logarithmic repartition of the hashes [4] Problems:

Unequal collision probability (half MAC addresses will set first bit ot one while only one will set the last bast to one) Very approximate for low numbers of MAC addresses (which is our case most of the time) BLOOM FILTERS Data structure useful for many applications Insertion and search in O(1) ...but false positives ...which we use for privacy purpose We aim to be able to say that a person may have been here, but never be sure about it Principle: about the same as bitmaps, but use several hashing functions spreading bits uniformly on the array of bits

  There is no miracle solution We aim to propose a privacy/utility tradeoff OBJECTIVES Short term: First, comparing the different methods Finding a good privacy metric Long term: Having a ready-to-use system with the same functionalities than existing Wi-Fi tracking systems, augmented with privacy-by-design DATA COLLECTION We need datasets to perform all our tests, containing logs of raw MAC addresses seen at a certain time at a certain place. Legislation forbids the collection of such datasets, as they contain personal identifiers Need consent of all concerned people difficult to set up Possible solutions: getting the consent of concerned people (one try at ACM Middleware, small dataset obtained) generate synthetic datasets from models PRIVACY METRICS We need metrics to quantify "privacy", in order to evaluate our methods Possible metrics are (non-exhaustive list): K-anonymity Collision rate: how many devices may be identified by the same identifier? entropy? Other considerations: Is the collision rate evenly distributed? What happens on extreme values? (e.g. very few number of passers-by) We have to determine which one (among these ones or other ones) best fits ours needs HASHING Principle: Using a simple cryptographic hash function, such as MD5 or functions of the SHA family, with no salt Problems:Easy to reverse in the case of MAC addresses[2] Almost no collision Almost useless

  aa:bb:cc:dd:ee:number of visitors (with m length of the filter, k number of hash functions, X number of ones) possible to know for sure that some MAC addresses were seen May still give bad results for low numbers of MAC addresses (tests ongoing)OTHER POSSIBILITIESUsing other phone characterisitics instead of MAC addresses (plenty of fingerprinting techniques exist)[5] Hashing with salts (keys), and destroying keys after a predefined period of time. Key destruction is not a trivial problem. DEPLOYMENT Simple tools: raspberry pis with Wi-Fi dongles Partnership with UrbaLyon Searching for partners with an infrastructure to share (electricity + network access) FUNDING Project founded by Academic Research Community (ARC), Rh ône-Alpes region (ARC 7).