Keywords: Trade liberalization, FTA, Asia, Latin America, CGE modeling JEL classification: F13, F15, C68

Recently, Asian and Latin American countries have been involved in a series of negotiations to liberalize trade and investment flows. This paper analyzes the potential impact of a Free Trade Agreement between countries of both regions, applying a world dynamic general equilibrium model (MIRAGE). The model includes a new way of modeling bilateral investment flows and bilateral investment agreements. Our results show that most countries will benefit from the agreement; however, Latin American countries' gains will be higher, especially when all Asian countries participate. Latin American countries will also gain from increased FDI inflows, mainly from developed Asian countries.

Introduction

During the last decade, there has been a proliferation of regional trade agreements (RTAs) worldwide. Asia and Latin America are part of this phenomenon, and even though South-South agreements are still rare, cooperation between countries from these two regions is on the rise. To date, there are 12 RTAs between Asian and Latin American countries, all of which have been signed in the last six years, and negotiations of six new free trade agreements (FTAs) are taking place. These agreements tend to increase the scope of traditional agreements, incorporating new issues such as investment, public procurement, and competition policy.

Trade and investment flows between both regions have intensified in recent years.

Asia's share in Latin American imports rose from 14 percent in 2000-2002 to 20 percent in 2006-2008, while Latin America has also become a more important importer for Asia, representing 1.2 percent of total Asian imports in 2000-2002and 2 percent in 2006[START_REF] Laborde | Procedure for implementing a consistent aggregator for tariffs in a CGE[END_REF](International Trade and Tariff Database-WTO 2010). One of the key countries behind these trends is China, which has become a main market for Latin American exports, especially of mineral and agriculture goods, and also a major provider of investment flows to Latin America [START_REF] Romero | Economics in Latin America Race Ahead[END_REF]. Other Asian countries, such as Japan and Korea, have also intensified their economic links with Latin American countries through an increase in investment projects in the region. On the Latin American side, Chile and Peru have deepened economic ties with Asian countries the most through the signing of several trade and investment agreements, while Brazil is the Latin American country with the largest outflows of foreign direct investment to Asian markets.

Asia and Latin America are two very different regions in terms of trade and development patterns. While Asian exports are highly concentrated in industrial goods, Latin America relies more on agriculture and mineral exports. These specializations, consistent with their reciprocal comparative advantages, also characterize interregional trade. These two regions differ in their trade policy; while Asia has followed a more open strategy, Latin America has only recently started opening its economy. However, trade protection is higher in Asia than in Latin America, especially for agricultural goods. For this reason, Latin American countries on average face higher tariffs on their exports to Asia than do Asian countries on exports to Latin America. Economic performance in terms of GDP growth has been greater for Asia than for Latin America over the last two decades (2 percent annual GDP growth at constant prices from 1990-2007 in Asia versus 1.4 percent GDP growth in Latin America during the same time period), whereas poverty indexes, although worrisome in both continents, are especially high for Asian countries such as India, Nepal, and Bangladesh.

The high level of protection and low level of integration between countries of both regions suggest that a trade agreement between Asian and Latin American countries would entail both economic and social benefits and would be an unprecedented phenomenon in terms of trade agreements. This paper examines the potential impacts of a free trade agreement (FTA) between Latin America and Asia using the MIRAGE computable general equilibrium (CGE) model of the world economy. We are interested in evaluating the potential effects of such a free trade agreement on trade and investment flows and the way these effects may boost economic growth. One of the channels by which trade liberalization can stimulate growth and development is through foreign direct investment (FDI). While traditional modeling of RTAs tends to focus on static effects and usually predicts only meager gains from liberalization, we study the potential impact of this trade integration scenario on foreign investment with the help of an improved version of the MIRAGE model of the world economy. In this new version of MIRAGE, the investment decisions of firms are distinguished from the investment decisions of households. Firms keep a share of their profits to reinvest in their sector and choose only the location of their investments. In our modeling exercise, we also improve the way tariffs are aggregated, applying a consistent tariff aggregator. We also model the implementation of Bilateral Investment Treaties (BITs).

Our results suggest that an FTA between Asia and Latin America would bring benefits to most members of the agreement, although gains would be higher for Latin America countries, which would experience an increase in exports to Asia and in investment inflows to the region. Latin American exports would increase mostly in highly protected agro-food sectors; as a consequence, unskilled rural wages would increase, suggesting a potential reduction in rural poverty. Asian exports to Latin America would increase in industrial sectors, reinforcing the current trade pattern between the regions.

In the next section, we present the methodology used to evaluate the potential impact of an FTA between Asia and Latin America. This includes a brief description of the applied CGE model and a more detailed description of the improvements introduced in this paper.

The results obtained under the different versions of MIRAGE are presented in Section 3.

Finally, Section 4 presents some conclusions and policy implications.

Methodological approach

This section provides a description of the methodology used in this study to evaluate the consequences of trade integration between Asian and Latin American countries, with the idea that this kind of agreement could have important implications for both trade flows and foreign investment. We start with a snapshot of the MIRAGE model of the world economy and a description of the special tariff aggregation used in this modeling exercise. This is followed by a detailed description of the modeling framework for investment and FDI and the baseline designed for this study. Finally, we present the scenarios that are evaluated in this paper.

The MIRAGE model of the world economy

MIRAGE is a multi-country, multi-sector computable general equilibrium model of the world economy. In each country, a representative consumer maximizes a CES-LES (Constant Elasticity of Substitution-Linear Expenditure System) utility function under a budget constraint to allocate his/her income across goods. The origin of goods is determined by a CES (Constant Elasticity of Substitution) nested structure following the Armington (1996) assumption. 1 In addition, Northern countries are assumed to produce higher quality industrial goods compared with those supplied by Southern countries. On the production side, value added and intermediate goods are complements under a Leontief hypothesis. The value added is a CES function of unskilled labor and a composite of skilled labor and capital; this allows for the inclusion of less substitutability between the last two production factors. In agriculture and mining, production also depends on land and natural resources. New capital is perfectly mobile across sectors, while installed capital is immobile. Skilled labor is perfectly mobile across sectors, while unskilled labor is imperfectly mobile across agricultural sectors and non-agricultural sectors. Total employment is constant. Investment is savings-driven and the real exchange rate is adjusted (through price adjustments) so that the current account is constant in terms of world Gross Domestic Product (GDP). This last assumption is particularly important in this study since tariff reductions will have positively correlated impacts on both imports and exports for every country. In this paper, we introduce three innovations in the standard version of MIRAGE model. First, we work with a different tariff aggregator. Second, we introduce modifications to the way we model FDI. Third, we also introduce the modelization of bilateral investment treaties (BITs).

Tariff aggregation

Historically, in order to introduce tariffs in CGE models, measures such as simple or trade-weighted average tariffs have been employed; however, these lack a theoretical foundation and may introduce significant biases in estimation. The most obvious problem with the trade-weighted average is that the weight on any tariff declines as the tariff rises, with very high tariffs having vanishingly small weights even when their trade-distorting impacts may be large. More recently, new approaches with rigorous theoretical foundations for this aggregation problem have emerged. [START_REF] Anderson | Measuring the restrictivenness of trade policy[END_REF] proposed a uniform tariff that yields the same welfare as the original differentiated tariff structure. In subsequent works [START_REF] Anderson | A New Approach to Evaluating Trade Policy[END_REF][START_REF] Anderson | The Mercantilist Index of Trade Policy[END_REF][START_REF] Anderson | Measuring the Restrictiveness of International Trade Policy[END_REF], they developed uniform tariff measures that are equivalent in their effects on the value of exports. The unifying feature of these aggregators is that they return the uniform tariff rate that yields the same value of a specific objective function as the actual, non-uniform tariffs. Using an atheoric approach, the MAcMapHS6 methodology [START_REF] Bouet | Assessing Applied Protection Across the World[END_REF] proposes to use an instrumental variable, the imports of a reference group, to reduce the endogeneity bias of protection at the bilateral level. Building on the Anderson-Neary approach, [START_REF] Bach | China and the WTO: tariff offers, exemptions, and welfare implications[END_REF] and [START_REF] Bach | Would the right tariff aggregator for policy analysis please stand up?[END_REF] proposed an approach to tariff aggregation in the context of structural economic models that mitigates many of the problems resulting from the use of atheoretic aggregators and showed that the implications of aggregation could be large for specific countries. However, they were only able to apply their approach to individual countries or regions. In a single-country model, a different tariff aggregator can be introduced into the expenditure and tariff revenue functions and used to solve for the welfare impacts of changes in tariffs. When this is done in a global model, however, a major difficulty arises because Walras's Law is no longer satisfied at the global level. When, for instance, a reduction in a particularly high tariff in one country results in a more rapid decline in expenditures than in tariff revenues, the country experiences a gain in welfare without any corresponding increase in income elsewhere. [START_REF] Anderson | Consistent Trade Policy Aggregation[END_REF] resolved this problem ingeniously by recognizing that the quantity indexes at domestic prices are different from quantity indexes at world prices. To take this into account, he notes that expenditure on aggregate good j at domestic prices must equal expenditure on the good at border prices plus the value of the tariff. In this paper, we implement this idea using the methodology proposed by [START_REF] Laborde | Procedure for implementing a consistent aggregator for tariffs in a CGE[END_REF] and already applied in Laborde, Martin, and van der Mensbrugghe 2009. Therefore, each tariff scenario implemented at the HS6 level on a bilateral basis is translated into two parameters that will be used in the model: i) a trade-weighted average (using ex-post weights) to capture the right tariff revenue aggregator and ii) the true price index of the imports to produce an expenditure-consistent aggregator and capture the quantity wedge at world and domestic prices. We report results using both this tariff aggregator and the traditional trade-weighted average tariff aggregator. We should expect smaller gains from liberalization when we introduce the latter, as it tends to underestimate high peaks in tariff structure.

Investment and Foreign Direct Investment

The way in which FDI is modeled in this study differs significantly from the usual MIRAGE FDI framework. Contrary to the standard framework of MIRAGE, and following [START_REF] Laborde | Does Foreign Investment Shape Trade Policies? A CGE Assessment of the Doha Stalemate[END_REF], we assume that households and firms exhibit different investment behaviors. In the standard version of MIRAGE, all firm profits are given to the household, which invests its savings across sectors and countries based on its preferences (calibrated on existing investment patterns) and the evolution of real return of investment. In this paper's approach, we maintain this household behavior unchanged; however, we assume that firms keep a share of their profits to reinvest in their own sector, being able to choose only the location of their investments. These two behaviors are designed to mimic the difference between portfolio investments and FDI, as shown in Figure 1.

Investment decisions by households and firms

Household Firms

Source: authors' elaboration

In dynamics, the most profitable sectors will invest more in themselves and will focus on optimizing the location of their investments. On the other hand, declining sectors will have fewer resources of their own; since households will not invest in them either, they will shrink.

The data on bilateral FDI flows and stocks employed in our modeling exercise have been built by CEPII (France) and are documented in [START_REF] Boumellassa | Bilateral and sectoral investment[END_REF].

As opposed to other data sources, this database is fully consistent, balanced, and suitable for use in a CGE framework. It is designed to be compatible with GTAP7.

FTAs are assumed to foster FDI among participants through a "mechanical" link between FDI and trade as well as through an important institutional component. Investor trust is reinforced by the strong commitments of countries participating in an FTA to liberalize trade (therefore securing trade channels for the future), harmonize rules, and, in most of cases, consider legal solutions for disputes. In addition, most FTAs involve several dispositions concerning FDI and lead to the implementation, or the reinforcement, of bilateral investment treaties (BIT).

In this paper, we consider the implementation of BITs between countries of each block to be complementary to the implementation of the FTA between both regions.2 To simulate this type of agreement, we introduce a shifter in the preference parameters of the investment function of both firms and households. The shifter is calibrated based on the estimated effects of BIT in gravity literature explaining FDI [START_REF] Bittencourt | Regional integration and foreign direct investment: the potential impact of the FTAA and the EU-MERCOSUR agreement on FDI flows into MERCOSUR countries: winners and losers[END_REF]. Ceteris paribus, bilateral investment flows are multiplied by the exponential of the coefficient in the BIT dummy when BITs are implemented, in comparison with the reference situation (no BIT). Concretely, we shock the preference parameter to obtain, ceteris paribus, the desired evolution of the share pattern. Simulations are performed both with and without this effect to assess the robustness of our results.

Baseline

A baseline is implemented from 2008-2025, which depicts world trade as it would be without a new multilateral agreement. In the baseline, we also implement main trade policy changes since 2004 such as ongoing WTO accession commitments, including those of the most recent members (Ukraine, Cape Verde, and Vietnam), an updated Japanese GSP (Generalized System of Preferences) scheme favoring LDC countries, modified bound tariffs on EU poultry, the 2007 EU enlargement to include Romania and Bulgaria, and the end of the EU EBA (Everything But Arms) regime for protocol products (sugar, banana, and rice).

Regional agreements such as SAFTA are also implemented. However, we do not include agreements under negotiation (for example, EU-India) or the India-ASEAN FTA. In addition, we do not implement a wide FTA inside each block in the scenario or in the baseline.

This baseline serves as a point of comparison for all scenarios. The results are reported for the year 2025. Results are presented as the percentage difference between the baseline and the scenario for a certain macroeconomic variable in 2025. The analysis does not account for the surge in world prices of energy and food products from 2004-2008. However, exogenous increases in active populations are included in the model, and each country's global factor productivity is affected so that GDP evolution, as described by the model, corresponds to the World Bank's GDP predictions.

Scenario Design

We focus on two simple trade scenarios:

• A complete free trade area between Asia and Latin America 3 is implemented from 2010-2014.

• A complete free trade area between the two regions is implemented (as in the scenario above), excluding the most developed Asian economies (namely, Japan and South Korea) We assume CES preferences across HS6 products belonging to one aggregated sector in the 3 Latin American countries/regions are Argentina, Andean Community, Brazil, Chile, Rest of Mercosur, Venezuela, and Central America, while in Asia, the countries/regions considered are China, Japan, Korea, Hong Kong, Singapore, ASEAN, South Asia, India, and Central Asia.

model, with an elasticity of substitution of 2. The latter value is a conservative assumption;

the lack of relevant econometric estimates makes it difficult to choose higher values on a robust ground, knowing that welfare effects increase significantly with the value of this parameter. Therefore, we can consider our estimates as lower bound (see [START_REF] Laborde | Measuring the Benefits of Global Liberalization with a Consistent Tariff Aggregator[END_REF] for a discussion of this parameter and sensitivity analysis).

It is important to emphasize that we do not include "exceptions" or sensitive products that will be not liberalized in the FTA design. Similarly, all tariffs are eliminated on goods and we do not consider the implementation of tariff rate quotas. Therefore, our assessment focuses on the maximum potential trade and welfare effects of trade liberalization between two regions.

Results

In the first subsection below, we present results obtained through the traditional version of the MIRAGE model of the world economy; in the second subsection below, we comment on results obtained with the new specification relating trade and foreign direct investment.

Results obtained through the traditional version of MIRAGE

Tables 1-4 present results of the evaluation of the following two scenarios: i) the implementation of a free trade area between Latin American countries and Asian countries and ii) the implementation of the same agreement excluding developed Asian countries (Japan and South Korea).

Table 1 presents the impact of a free trade area between Latin American countries and Asian countries on macro variables; all countries concerned in the agreement benefit from it except the Andean countries, Central America, and Venezuela in Latin America and India, South Asia, and ASEAN in Asia. The loss of real income for some countries is not a surprise and may result from trade deflection effects being greater than trade creation effects (see [START_REF] Viner | The Customs Union Issue[END_REF] for theory of customs union). Indeed, these regions are hurt by a deterioration of terms of trade. For these Latin American countries, imports increase substantially from Japan (118 percent in Venezuela and 57 percent in Andean countries), Korea (101 percent and 75 percent, respectively) and China (99 percent and 79 percent, respectively) and fall from Latin American partners (especially MERCOSUR countries and Chile) and third-party trade partners (NAFTA and European countries). Asian regions strongly increase imports from all Latin American countries, especially Argentina, Brazil, and the Andean Community, and reduce imports from all other regions.

In terms of positive impacts, gains from the agreement are greater for Latin American countries, with substantial gains for Argentina (+0.7 percent), Chile (+1.2 percent), and Rest of Mercosur (Paraguay-Uruguay +2.6 percent). Exports increase substantially in volume in the case of Central America (+10.4 percent), Brazil (+7.8 percent), Rest of Mercosur (+6.4 percent), and Andean countries (+6.2 percent). These countries experience the highest increase in exports from specific sectors whose markets are practically closed in some Asian countries in the reference year; this is the case for exports of rice from Brazil to Japan, oilseeds from Rest of Mercosur and Andean countries to Korea, and sugar for most Latin American countries to Japan. As far as Asian countries are concerned, the most benefited region is Central Asia, with welfare increases of 1.3 percent and export increases of 3.3 percent. All other Asian economies also increase their exports, but to a much lower extent than Latin American countries.

The impact on exports from regions not participating in the agreement is, as expected, negative, although this result does not have a significant negative effect on welfare. The most harmed regions not participating in the agreement are NAFTA, with a 0.5 percent fall in exports, and Sub-Saharan Africa, with the highest fall in welfare (-0.04 percent) and in real GDP (-0.02 percent). Table 2 shows how production in volume is affected by the agreement with an agrofood, industry, and services split. It confirms the expectation that this agreement will reinforce the production specialization of Latin American countries in agro-food sectors, while Asian countries will raise their allocation of production in industry. Trade liberalization leads to a reinforcement of the sectors with comparative advantages in each region-agriculture in Latin America and manufacturing activities in Asia.

The increase in real value added is substantial in the case of agro-food in Brazil (Rice: 119 percent, Beverages and Tobacco: 25.7 percent, and Sugar: 23.5 percent), Argentina (Rice:

21.8 percent, Vegetal oils: 18.6 percent, and Oilseeds: 16.9 percent), and Rest of Mercosur (Oilseeds: 47.9 percent and Sugar: 19.1 percent). It is noteworthy that the decline of industrial production is significant in Brazil, Argentina, Chile, and Andean countries. This suggests that this type of reform may entail some political costs. In Asian countries, value added in industry increases mainly for Textiles (ASEAN: +1.2 percent and South Asia: +1.1 percent), Wearing apparel (India: +3 percent, South Asia: + 1.1 percent, and ASEAN: 1.1 percent), and Leather (India: +1.9 percent). In Korea, increase in production is seen in the agriculture sectors, mainly vegetal oil and other cereals.

When we exclude developed Asian countries from the agreement, the results are similar but, due to reduced trade creation, the increase in real income is lower for Argentina, Brazil, and Rest of Mercosur since they do not benefit from improved access to Japan and South Korea. Some larger Asian economies, such as ASEAN and China, benefit from the fact that developed countries are not part of the agreement; they gain increased access to Latin American markets without having to compete with Japan and South Korea. Exports to all Latin American markets increase by more than 50 percent for both China and ASEAN, compared with increases lower than 2 percent, or even decreases in exports, when Japan and Korea are part of the agreement.

In Table 3, we see that, when excluding Japan and South Korea, the pattern of specialization is the same but is less intense than when these two countries are part of the agreement (compare figures for Argentina, Brazil, and Rest of MERCOSUR in Table 2 andTable 3). In the case of Rest of Mercosur (Paraguay and Uruguay), the impact on industrial production is now positive, so the political cost would not be lower. Excluding them from the agreement annuls any production effect on Japan and South Korea and has no differentiated impact on production specialization for the rest of Asian countries, which still increase their industrial production.

0.0 -0.3 -0.0 -0.0 -0.2 India Asia 0.2 0.0 -0.8 0.2 0.0 -0.8 Japan Asia 0.2 0.1 -4.6 -0.0 -0.0 -0.1 Korea Asia 0.3 0.3 -0.2 0.0 0.0 -0.0 Rest of Asia Asia -0.0 -0.0 -0.4 -0.0 -0.0 -0.2
South Asia Asia 0.0 0.0 -0.2 0.0 0.0 -0.2

Source: MIRAGE and authors' calculations

Table 5 and Figure 2 show how the impact on welfare and trade varies when we introduce modifications in the model-changing the tariff aggregator (CTA), changing the FDI modeling framework (CTA+FDI), and modeling Bilateral Trade Agreements between both regions (CTA+FDI+BIT). As with any trade policy assessment, the results presented in the previous section (TTA) are sensitive to the tariff aggregator considered. When we introduce the consistent tariff aggregator described in Section 2.2, gains for most countries from the FTA are higher, except in certain cases such as Chile and, to a lower extent, Rest of Mercosur, which originally present a more homogenous protection structure. As previously discussed, the average tariff tends to be higher when we apply the consistent tariff aggregator compared with when we apply the traditional trade-weighted average, especially when the original tariff structure presents high variance. For this latter reason, Brazil and Central America have higher gains from liberalization with the new tariff aggregator, while Chile and Rest of Mercosur have lower gains from liberalization and suffer from stronger preference erosion mechanisms. Among Asian countries, Korea reports higher welfare gains with the new tariff aggregator, also associated with an initially more disperse tariff structure. The higher average tariff among the countries participating in the agreements explains the higher increase in bilateral trade flows when we change the tariff aggregator in the model (see Figure 2). Impact of Free Trade between Latin American countries and Asian countries (with and without developing countries) -Bilateral trade flows (in value at FOB prices)-2020

Source: MIRAGE and authors' calculation

Trade flows increase more when we also modify the FDI framework within the model; however, this change is not significant, whereas the impact on real income and especially on GDP is stronger, especially for those regions that become FDI captors. Gains under this framework are mostly associated with increases in investment and production and, to a much lesser extent, with changes in trade flows.

The positive impact on welfare in most countries/regions is more pronounced when we also consider the negotiation of BITs among both regions. This occurs because, in this case, bilateral FDI flows increase strongly with the shift in investor preferences. Thus, introducing BITs in the agreement implies additional welfare gains for the participants. Andean countries, for example, experience welfare increases instead of losses, and the same happens for Japan. Welfare still declines for Venezuela, although to a lesser extent. BITs reinforce the increase in trade flows, although the increase is not sharp. Except in Central America, all Latin American countries and regions increase exports (in value) when BITs are included in the agreement. When capital flows increase between the two regions, bilateral trade costs fall and trade rises. However, when BITs are implemented, service sector exports from Asian countries (especially developed Asian economies) to Latin America in fall.

Trade rises in those sectors that already expanded as a consequence of the trade agreement. However, there are some exceptions. In the case of Rest of Mercosur, for example, primary exports increase when BITs are introduced, whereas they fall in the rest of the simulation scenarios.

Latin American countries benefit from an increase in FDI inflows under the new FDI modeling framework. Again, except for Central America, all regions in Latin America increase GDP when foreign investment is introduced in the model, and even more when the FTA includes BITs. Brazil, Argentina, Rest of Mercosur, Andean countries, and Venezuela become FDI inflow captors; in all these economies, inward FDI increases by more than 1 percent (in the case of Rest of Mercosur, the increase is almost 7 percent). When we also introduce BITs in the model, the increase in FDI inflows in those countries is boosted, reaching 20 percent in the case of Rest of Mercosur (see Figure 3). In absolute terms, though, the biggest economies in Latin America (Brazil, Andean countries, and Argentina) are the "winners" in capturing new investment inflows, which is in line with what has been found in empirical studies [START_REF] Bittencourt | Regional integration and foreign direct investment: the potential impact of the FTAA and the EU-MERCOSUR agreement on FDI flows into MERCOSUR countries: winners and losers[END_REF]. 4 It is worth mentioning the case of Venezuela, which gains from an increase in FDI inflows but also increases FDI outflows as a result of an FTA with BIT with all Asian economies. These results are obtained when developed Asian countries are included in the agreements, as they become the main FDI outflow providers. The situation changes radically when those countries are excluded. In this case, even though bigger Latin American economies still capture FDI inflows, the increase is now much lower.

4 However, this effect might be underestimated because in the model, we are not considering economies of scale; therefore larger markets do not have an advantage per se.

BITs increase FDI inflows for the participants of the agreement, especially for Latin American countries and even for those countries with previous BITs with Asian economies (such as Argentina or Chile). For those countries without previous BITs with Japan and Korea (such as Brazil, Andean countries, and Rest of Mercosur), these two countries become the main FDI inflows providers, whereas in the case of Argentina and Chile, inflows come mainly from Hong Kong and Singapore.

At the same time, Latin America loses investments from Europe and NAFTA. With more investments coming from "preferred" partners, the rate of return of capital in Latin American countries goes down (see Figure 4); these markets become less attractive to third-party investors (creating a crowding-out effect on third parties). This last effect dominates the positive effect that BITs may have on investment from other countries through increased growth and higher profits.

As already mentioned, Asian economies (especially developed Asian countries) increase FDI outflows, especially when BITs are included in the agreement. However, while there is investment creation, there is also a redirection of FDI and some regions lose their position as recipients of Asian FDI, such as ASEAN, European Union, and NAFTA, therefore reducing real income. Impact of Free Trade between Latin American countries and Asian countries-Real returns to capital -% Scenario/baseline -2020

Source: MIRAGE and authors' calculations When Japan and South Korea are excluded from the agreement, welfare gains are smaller for most Latin American countries, and there are welfare losses for Central America and Venezuela. Bilateral trade flows increase much less under this scenario (for any bilateral trade flow model specification discussed, see Figure 2), while FDI inflows to Latin America increase to a much lesser extent, as the main investment flows comes from Japan and Korea (Figure 6). Regions that are not part of the agreement (Russia, Sub-Saharan Africa, NAFTA, and European Union) also benefit when Japan and South Korea do not participate. In the case of NAFTA and European Union, this is caused by a lower negative impact on exports to Latin American markets.

Sub-Saharan African countries lose less FDI inflows, while Russia gains from increased exports to Asian countries (especially the developed countries).

Figure 5 Impact of Free Trade between Latin American countries and developing Asian countries-Welfare-% Scenario/baseline -2020

Source: MIRAGE and authors' calculations

Figure 6

Impact of Free Trade between Latin American countries and developing Asian countries-FDI flows (no BITs)-% Scenario/baseline -2020

Source: MIRAGE and authors' calculations

Concluding remarks

In this paper, we study the opportunities for trade and investment that a free trade area between Latin American and Asian countries could imply. Such an agreement is particularly interesting because Latin America is specialized in agro-food products, which it predominantly exports, while Asian agricultural markets are protected. Similarly, Asia already intensively exports industrial products, while industrial protection in Latin America is still significant. Thus, a free trade agreement between both regions could lead to trade creation. South-South agreements, like the one that Asia and Latin American regions could be engaged in, are still uncommon, although there have been some examples in the last few years. Thus, analyzing the potential impact of this type of agreement becomes a relevant exercise which has not been done previously.

Our results, obtained through different and improved versions of the MIRAGE model of the world economy, show that the implementation of a free trade agreement between Asia and Latin America brings benefits for almost all countries directly concerned. Gains are especially high for Latin American countries, which substantially increase their exports of agricultural commodities and food. The agreement leads to a reinforced pattern of specialization, with Latin America producing agro-food products and Asian countries specialized in industry. If developed Asian countries (namely, Japan and South Korea) are not included in the free trade area, the gains for Latin American countries are reduced. However, developing Asian countries benefit more from the agreement if Japan and Korea do not participate, as they gain increased access to Latin American markets.

We should keep in mind that in these scenarios, we are not including sensitive products; therefore we are considering the maximum potential gains from an agreement between Asia and Latin America. In reality, we might expect lower gains because Latin American exports increase in traditionally sensitive sectors for Asian countries (rice, dairies, soya, and sugar) and vice versa (textiles and wearing apparel), these sectors facing a high probability of only partial liberalization.

We also simulated a free trade agreement that also includes a bilateral trade agreement between both regions, as most recent South-South agreements incorporate such an agreement.

The new generation of agreements has a positive effect on Latin America countries, where welfare increases as a consequence of trade creation and also as a consequence of higher FDI flows. These results hold when developed Asian countries are part of the agreement. If Japan and South Korea do not participate in the agreement, gains are much smaller, although still positive for most Latin American countries. However, developing Asian economies do not benefit from additional gains when the agreement also includes BITs except when Japan and Korea are not part of the agreement. In this latter case, developing Asian countries gain from increased FDI inflows, partly because Japan and Korea, since they no longer have agreements with Latin America, can increase investment in the rest of Asia. These results suggest that improving the modeling framework to introduce FDI and BITs is extremely important, especially when analyzing the effects of trade agreements that go beyond liberalization of trade in goods and services. Our results also show that with a consistent tariff aggregator, we obtain a more pronounced impact of FTA on trade flows due to increased initial tariff levels in most countries participating in the agreement.

Figure 1

 1 Figure 1

  since these two countries are the only Asian OECD countries and a FTA between High Income Countries and Middle Income Countries is still uncommon.These two scenarios are run first with the traditional version of MIRAGE (TTA) and then with the following changes: i) change in the consistent tariff aggregator (CTA), ii) change in FDI framework (FDI), and iii) change in shifter parameter to consider the implementation of BIT(s).Using the highly disaggregated information (5,113 products and more than 160 countries) of the MAcMapHS6 version 2[START_REF] Boumellassa | A Picture of Tariff Protection Across the World in[END_REF], we compute the evolution of the trade-weighted average tariff -but with endogenous trade weights-to have the correct tariff revenue aggregator and the true price index of imports at domestic prices (the correct expenditures aggregator) at the aggregation level of the model.

Figure 2

 2 Figure 2

Figure 3

 3 Figure 3Impact of Free Trade between Latin American countries and Asian countries-FDI flows -% Scenario/baseline -2020

Figure 4

 4 Figure 4

Table 3

 3 Impact of Free Trade between Latin American countries and Asian countries (Japan and South Korea excluded) -Production in volume -% Scenario/baseline -2020

				Rest of	Andean	Central					South
		Argentina Brazil	MERCOSUR	countries	America	China	ASEAN	India Japan	Asia
	Agro-
	food	4.43	4.46	0.85	0.55	-0.04	-0.11	-0.14	-1.22 -0.01	-0.39
	Industry	-1.46	-1.63	2.73	-1.12	0.06	0.13	0.33	0.73	-0.02	0.57
	Services	0.36	0.07	-0.05	0.06	0.00	0.01	-0.09	-0.15 -0.00	-0.07
	Source: MIRAGE and authors' calculations
	(according to ECLAC estimates, 52.2 percent of the rural population in 2008 was poor versus
	27.6 percent of the urban population), an increase in wages for the agricultural sector may
	contribute to a reduction of poverty in the continent as a whole. Rural poverty is also higher
	in most Asian countries (World Development Indicator-World Bank, 2010); thus the
	specialization in manufacturing and the consequent fall in agricultural wages do not
	contribute to a reduction of poverty in Asia.

Unskilled real wages in Latin American countries, especially in the agricultural sector, increase as a result of the expansion of agro-food sectors, as shown in Table

4

. The increase is again particularly important for Rest of Mercosur countries and Chile and when developed Asian countries are part of the agreement. For most Asian countries, on the other hand, unskilled wages in the agricultural sector fall as a consequence of the specialization in industrial sectors. Given that poverty in Latin America is more concentrated in rural areas

Table 4

 4 Impact of Free Trade between Latin American countries and Asian countries-Wages -%

	Scenario/baseline -2020
			FTA including Japan and Korea	FTA excluding Japan and Korea
	Region	Region	Skilled real wages	Unskilled real wages	Unskilled real wages in agriculture	Skilled real wages	Unskilled real wages	Unskilled real wages in agriculture
	Andean Comm.	Latin America	-0.1	0.3	2.5	-0.2	-0.0	0.7
	Argentina	Latin America	0.6	1.1	6.3	0.5	1.0	5.6
	Brazil	Latin America	0.1	0.6	9.7	0.1	0.3	5.5
	Central America	Latin America	0.9	1.2	2.4	0.7	0.8	0.9
	Chile	Latin America	1.1	2.1	16.5	0.2	0.4	2.0
	Rest of Mercosur	Latin America	1.8	5.2	16.6	1.1	2.0	4.8
	Venezuela	Latin America	-0.3	-0.1	-0.1	-0.3	-0.2	-0.3
	ASEAN	Asia	0.1	0.0	-0.6	0.2	0.1	-0.4
	Central Asia	Asia	0.4	0.2	0.1	0.4	0.2	0.1
	China	Asia	0.1	0.1	-0.1	0.1	0.1	-0.0
	Hong Kong and
	Singapore	Asia	0.0

Table 5

 5 Impact of Free Trade between Latin American countries and Asian countries-Welfare -% Scenario/baseline -2020

	Region	Region	TTA	CTA	CTA + FDI	CTA + FDI + BIT
	Asia		0.05	0.05	0.05	0.06
	Latin America		0.20	0.51	0.52	0.68
	ASEAN	Asia	-0.03	-0.02	-0.03	-0.04
	Central Asia	Asia	1.31	1.47	1.46	1.45
	China	Asia	0.04	0.03	0.03	0.02
	Hong Kong & Singapore	Asia	0.03	0.05	0.04	-0.21
	India	Asia	-0.01	-0.01	-0.01	-0.01
	Japan	Asia	0.03	-0.01	-0.00	0.03
	Korea	Asia	0.16	0.33	0.33	0.34
	Rest of Asia	Asia	-0.02	-0.20	-0.20	-0.19
	South Asia	Asia	-0.03	-0.05	-0.05	-0.04
	Andean Community	Latin America	-0.11	-0.06	-0.02	0.14
	Argentina	Latin America	0.67	0.90	0.95	1.23
	Brazil	Latin America	0.27	0.94	0.93	1.17
	Central America	Latin America	-0.21	0.10	0.11	0.11
	Chile	Latin America	1.20	0.60	0.61	0.60
	Rest of Mercosur	Latin America	2.60	1.61	1.61	1.82
	Venezuela	Latin America	-0.31	-0.29	-0.23	-0.10
	Source: MIRAGE results (various specifications) and authors' calculation
	Note: TTA: original MIRAGE version; CTA: consistent tariff aggregator; CTA+FDI consistent tariff aggregator plus new
	way of modeling FDI; CTA+FDI+BIT: consistent tariff aggregator plus new way of modeling FDI+ BITs

  In this context, introducing BITs in the agreement does not have any effect on FDI flows. Most Asian economies are better off when developed Asian countries are not part of the agreement; ASEAN and China have welfare increases, while Rest of Asia has a lower welfare loss. These gains are associated with increased FDI inflows into those economies, partly because Japan and Korea, since they no longer have agreements with Latin America, can increase investment into the rest of Asia. Developing Asian countries also increase their exports when developed countries are not part of the agreement. India increases exports of vegetal oils and oilseed to Korea, while China increases rice and meat exports to Japan.

The MIRAGE model is based on GTAP Armington elasticities, which are low compared with those used in other models (for example, the World Bank's LINKAGE model).

If several countries have already enforced BIT, the FTA scenario will not have direct effects on their FDI pattern. However, these countries may suffer negative consequences through an FDI dilution effect, as countries with new BTI become more attractive to foreign investors.


Marwen Nouri

Emmanuel Marilly

Nicole Vincent

MOVING OBJECT SELECTION BASED ON AN ACTIVE CURVE APPROACH

Keywords: Tracking, Interactive Methods, Video Objet, Scribbles propagation

Recently, many innovating image segmentation approaches came to deal with the extraction of meaningful objects. The majority of these approaches need some user hints, such as scribbles designating the object to extract. This help to avoid a semantic gap. In the case of video object segmentation, drawing scribbles on each frame is a very long process. Scribbles drawn on one frame must be propagated automatically in the remainder of the video to make object extraction possible.

In this paper, a new framework for interactive video object selection is described. This framework is built upon active curve based scribbles propagation. Scribbles drawn by the user on the first frame are considered as curves. These curves are propagated automatically by our method on the next frames to designate the same object as the one designated by the user. A spatiotemporal optimization is introduced to ensure a coherent propagation.

INTRODUCTION

Video authoring is widely used in the context of movie production. This is a fastidious task generally done by professionals. With the raising of video sharing platforms e.g. YouTube, anyone is able to create his videos. Do-it-Yourself tools help to lower the barrier of video creation. Video creator profile is changing from professional to basic user, who needs simple tools to assist him. One of the most complicated tasks in video creation and authoring is object extraction and composition. Many interactive object extraction approaches [START_REF] Wang | Interactive video cutout[END_REF][START_REF] Baker | Lucas-Kanade 20 years on: A unifying framework[END_REF][START_REF] Bai | Fig. 6. (a) The user points out the man by drawing two scribbles on the first video frame[END_REF] allow user to extract an object from an image or from a video. Some of these approaches need just few scribbles drawn by user, designating the object to be extracted. To extract a video object, one interaction possibility is to draw scribbles frame by frame. By this way the needed interaction is very intensive and therefore too boring and time consuming. Tracking systems can be helpful to reduce the user efforts.

Motion analysis and tracking are essential tasks for most video processing algorithms. Object tracking has been a popular topic in research literature since several years. Some methods have been adapted in different approaches. We can mention optical flow for feature based approaches [START_REF] Etyngier | Active contour based image segmentation using machine learning techniques[END_REF][START_REF] Shi | Good features to track[END_REF][START_REF] Wang | Interactive video cutout[END_REF] and active contours for contour based approaches [START_REF] Lefevre | Real time multiple object tracking based on active contours[END_REF][START_REF] Lowe | Object recognition from local scaleinv-ariant features[END_REF]. To get an efficient system, some tracking approaches use models or manual interaction. This allows to deal with semantic gap and to remove confusions. The tracking method we are proposing takes place among methods requiring user hints. These methods are known as interactive methods. Interaction is classified into three categories, based on the tool used to select or to designate the desired object: spatiotemporal volume based, contour based and scribbles based. Spatiotemporal volume or 2D+t interaction methods allow user to add hints directly in video volume [START_REF] Wang | Interactive video cutout[END_REF]. These approaches are not natural to be used and visualizing 2D+t is very confusing. In the contour based methods [START_REF] Baker | Lucas-Kanade 20 years on: A unifying framework[END_REF], user must define the contour of the object of interest by placing points on the object boundary. These methods allow getting high level information: a silhouette. But they require much time during the interaction step and are not easy to use for basic user. The third category of interaction methods [START_REF] Bai | Fig. 6. (a) The user points out the man by drawing two scribbles on the first video frame[END_REF] are based on scribbles drawing. Scribbles allow user to point out an object in a non-rigorous and natural way. The object is roughly designated, one or two scribbles can be sufficient for doing that. Refinement can be done interactively to get the desired selection. Based on these few scribbles, some segmentation or matting methods [START_REF] Baker | Lucas-Kanade 20 years on: A unifying framework[END_REF] are able to separate efficiently an object from the background.

In this paper, we proposed an interactive method, which aims at tracking a moving object. The user is asked to designate an object of interest by drawing scribbles (or curves). Then, the problem is to propagate these scribbles in next frames while designating the same object. Section 2 describes the curve propagation problem and the proposed active curve modeling. Section 3 presents and discusses the different forces we defined to govern the propagation. Experiments and results are presented in section 4.

SCRIBBLES PROPAGATION

Our method aims at propagating scribbles drawn on a video frame to the remainder of the sequence. For this purpose we chose an active curve modeling. First, we will explain the characteristics and the problems of propagating a curve. Then, we will expose the active curve method, its properties and, based on it, how our problem is solved.

Curve characteristics and propagation

Propagating a hand drawn curve along the different video frames consists in tracking a set of points. Standard point based motion estimation methods, such as [START_REF] Irani | Multiframe correspondence estimation using subspace constraints[END_REF], do not allow a correct propagation of the curves points through a large number of video frames. To be correctly tracked, points must be illegible to criteria. This is the case of point of interest presented in [START_REF] Kass | Snakes: Active contour models[END_REF]. Moreover, due to the initial curves properties (the way and where the drawing is done), tracking errors will be propagated and accumulated progressively frame after frame. This will decrease the tracking or the propagation quality. Point based tracking is sensitive to texture similarity or aperture problems. Indeed, the curves points are not geometrically independent. Processing points independently can quickly become incoherent. We suggest processing all the points as a whole, as a curve.

What are the characteristics and the functionality of the curve we want to propagate? This question is implicit to the user who wants to select specific regions to point out an object. What are the properties enabling to propagate the curve while preserving its functionality? This curve crosses several regions that compose the selected object. The curve is usually located at the middle portion of these regions as shown in Fig. 1. Users drawing is usually coarse; security leads him to stay away from the objects edges.

To point out the same object in next video frames, the curve must stay in the selected regions and must be located in the middle of these areas in order to reduce the drift.

Three constraints have been identified, allowing the curve propagation, that are:

• If the selected object moves, the curve has to move accordingly, • The characteristics of crossed regions must be conserved, however, the evolution of these regions must be taken into account, • The curve must move towards areas as locally homogeneous as possible, in order to minimize errors and to converge towards the middle of each region. In our case, no initial assumptions can be done on the curve. As they are too global, some models like Bezier curves or splines dont seem flexible enough to enable curve propagation, considering our constraints. To perform a coherent propagation, these new constraints must be introduced to govern scribbles evolution. We define forces and the energy functional leading to position the curve on the next frames. Estimating the position of the curves in next frames is then done by an energy minimizing process based on greedy algorithm [START_REF] Williams | A Fast Algorithm for Active Contours and Curvature Estimation[END_REF]. It is an active curve based approach.

CONSTRAINTS MODELING

To ensure a coherent propagation of scribbles points and to make them evolve while designating the same object -a set of heterogeneous areas-through video frames, we define a set of energies. First, we model the forces, associated with the curve itself and then with image data, according to the defined constraints.

Internal forces

Conventionally, the internal used forces are related to the curve bending. They are: uniformity and curvature forces. The uniformity force associated with its energy functional E unif ormity tries to maintain the cohesion of curves points and therefore standardize the distances between each pair of successive points. The curvature energy E curve influences the rigidity of the curve. These energies functional drive curve shape and define how it can change over the evolution. Weights ω 1 and ω 2 are used to let the curve evolution have a membrane like behavior or thin-plat like behavior. On each point p, the internal energy can be written as:

E internal (p) = ω 1 E unif ormity (p) + ω 2 E curve (p) (1)

External forces

The definition of external forces is more sensitive. It is directly related to the nature of the problem. To get a coherent tracking system, which selects the same object in the successive frames, we decided to model the constraints defined previously by three forces:

• One is related to the estimated motion of each point,

• Another is related to the local color similarity,

• The last one indicates a privileged direction for propagation.

The movement of an object can be the composition of different movements from different parts of it. So, locally based motion estimation at each point is necessary to ensure that the overall curve is committed to the movement. Let p t be the optical flow [START_REF] Wang | Interactive video cutout[END_REF] estimated image of a curves point p t from frame t. We minimize the Euclidean distance between p t and p t+1 , the new points curve position in frame t+1. This energy formula is:

E f low (p) = |p, p | (2)
Between frames at time t and t + 1, the point must remain in the same part of the object. The area may be color uniform, but it also can be characterized by a texture. Characterization of the texture would be too time-consuming, so we chose to limit the study to the average color in a neighborhood of each curves point. We chose CIE Lab color space, which is composed from three components L, a and b. This color space allows us to distinguish between luminance and chromatic components of color. One curves point p t will then evolve to a new position with a similar color while including some tolerance to illumination change. The color similarity energy is calculated using a weighted Euclidean distance. The average color is denoted cm. Then the energy formula is:

E color (p) = (cm pt (a) -cm p (a)) 2 +(cm pt (b) -cm p (b)) 2 + 1/4 * (cm pt (l) -cm p (l)) 2 (3)
The last energy, we want to introduce, comes from the assumption that the user lacks precision when drawing the scribbles. Indeed, the user tends to draw the scribbles while trying to stay well within the middle zones of the different objects regions (which prevents him from getting out of the object). The curve must also reproduce this effect. So to answer this third constraint, we detect the locally homogeneous region around the curve, depending on the color of a segment with a direction orthogonal to the curve in each point (Fig. 3). Our goal, starting from the state of a point on the curve at time t, is to privilege the propagation in one direction rather than the others. Therefore, we can make the point to stay in the homogeneous zone to which he belonged. This energy will push points to an area of greater homogeneity, as shown in Fig. 4. To calculate this energy, we estimate the normal to the curve at each point p t , and calculate a similarity line segment. This segment associated with p curve is the maximum segment of uniform color. That is to say, all its points colors are similar to the p curve color. Maximum concerns the length of the segment. The extremities of this segment are the limit tolerance points. p lt denotes the extremity which is farthest from p t .

E privDir (p) = |p, p lt | (4) The external energy is composed from three weighted terms, finally:

E global (C) = p∈C (ω 1 E unif (p) + ω 2 E curv (p) + ω 3 E f low (p) + ω 4 E color (p) + ω 5 E privDir (p)) (5)
The relative weights have been determined experimentally as usually done in active energy minimizing based systems and result on different videos are shown in the next section using the same set of weights. Our system proposes a graphical user interface allowing user to draw one or many scribbles at any frame of a video to point out an object. Then scribbles are propagated automatically in a real time processing. Therefore user can interact at any time to point out a new region which was not visible at the beginning of the video. Our final results are best seen in video form, though we show several still images for example in this section.

EXPERIMENTAL RESULTS

We tested our approach on three standard video sequences (640x480x30) from the literature [START_REF] Williams | A Fast Algorithm for Active Contours and Curvature Estimation[END_REF][START_REF] Baker | Lucas-Kanade 20 years on: A unifying framework[END_REF] (Fig. 5,6). Our algorithm is designed to handle dynamic backgrounds as in Fig. 5 or Adam Lib sequence. Measuring objectively a success of systems like our presented one is difficult. One possible approach is based on the number of frames in which the initial designated object continues to be pointed out by our algorithm. This information is got from the final user. To compare our method, we implement an optical flow based scribbles propagator, denoted OFBP. I. Handling optical flow errors combined with sudden illumination must be improved on further work. This can cause confusion in our system as happens after frame 25 of walking man sequence.

CONCLUSION

In this paper, we showed a new approach for hand drawn curve propagation. It consists in using active curves model to formulate the problem of video object selection. This allows user driven designation of objects in videos. Our contributions consist on the formulation of scribbles propagation as an active curve model and the definition of the different related forces in order to obtain a more accurate video tracking.

Our algorithm can be further improved by adding features such as texture or by using a more recent and accurate optical flow estimator. We are currently focusing on this improvement and studying the potential of our approach in two elds: video matting and human actions classification.

Fig. 1 .

 1 Fig. 1. (a) Example of a scribble drawn by the user. (b) A set of curves points representing discretized scribble.

Fig. 2 .

 2 Fig. 2. (a) Example of a scribble drawn by the user. (b) A set of curves points representing discretized scribble.

Fig. 3 .

 3 Fig. 3. (a) Similarity line segment drawn on each point of the curve. (b) Zoomed view of (a).

Fig. 4 .

 4 Fig. 4. Privileged direction force.

Fig. 5 .

 5 Fig. 5. (a) Three scribbles drawn at frame 1 by the user to designate the women in the video. (b)(c)(d) The respective results of propagating scribbles from frame a to frames 8, 23 and 30.

  Fig. 5a, 6a show two examples of scribbles that we want propagate. OFBP fails even on basic cases as shown on Fig. 2. Our results are shown on Fig. 5, 6 and compared to OFBP implementation in Table

Table 1 .

 1 The number of frames in which the initial selected object is still designated.

		Amira Adam lib (29) Walking man
	OFBP	11	26	5
	Our method	30	29	25


Mathieu Avanzi
email: mathieu.avanzi@unine.ch

Anne Lacheret-Dujour

Bernard Victorri
email: bernard.victorri@ens.fr

A Corpus-based Learning Method for Prominence Detection in Spontaneous Speech

Keywords: prominence, discourse genre, corpus-based learning method, automatic detection

The aim of this paper is to present a software tool called ANALOR, which allows semi-automatic prominence detection in spontaneous French. On the basis of a manual annotation performed by two experts on a 70-minute long corpus including different regional varieties of French (Belgian, Swiss and metropolitan French) and various discourse genres (from read speech to spontaneous conversations), our system conducts a learning-method in order to determine the best thresholds for prominence prediction. This procedure appreciably improves detection, with consistency between automatic identification and the human labeling rising from 75.3 without training to 79.1 of f-measure after corpus-based learning.

Introduction

Nowadays, the automatic detection of prominence is considered by experts as an international challenge for the processing and linguistic analysis of spoken corpora, whatever the linguistic topic is (intono-syntactical rules, discourse/prosody interface, pragmatic effects of accentuation, marking of expressivity and emotion, etc.). Traditionally, automatic prominence detection has been based on (i) manual annotation, which is used as a reference for the automatic learning step and the development of a prosodic model of discourse; (ii) in-depth knowledge of the acoustic correlates of prominence perception. Many studies have addressed the problem of prominence detection over the last decade, and algorithms are still emerging [START_REF] Tamburini | An Automatic System for Detecting Prosodic Prominence in American English Continuous Speech[END_REF] [START_REF] Rosenberg | Detecting pitch accent using pitch corrected energy-based predictors[END_REF], particularly for French [START_REF] Avanzi | A Tool for Semi-Automatic Annotation of French Prosodic Structure[END_REF][4] [START_REF] Obin | Prominence model: a probabilistic framework[END_REF] [START_REF] Obin | Comparaison de trois outils de détection semi-automatique des proéminences dans les corpus de français parlé[END_REF]. In this paper, we present one of these algorithms (ANALOR), focusing on the learning methods and the theoretical prerequisites underpinning its constitution.

Comparing three systems for French

The earliest studies on the perceptual and automatic identification of prominence in French were conducted within the PFC Project ( [START_REF] Durand | La phonologie du français contemporain: usages, variétés et structure[END_REF] [START_REF] Poiré | La perception des proéminences et le codage prosodique[END_REF]), and were continued by an informal consortium of linguists in a certain number of publications (see [START_REF] Avanzi | C-PROM. An Annotated Corpus for French Prominence Studies[END_REF] for more details). They gave birth to three systems: ANALOR (see [START_REF] Avanzi | A Tool for Semi-Automatic Annotation of French Prosodic Structure[END_REF] and §3 below for the most recent description of the tool), PROSOPROM [START_REF] Goldman | A Methodology for the Automatic Detection of Perceived Prominent Syllables in Spoken French[END_REF] and IRCAMPROM [START_REF] Obin | Prominence model: a probabilistic framework[END_REF]. A study comparing the performances of these algorithms on the basis of a 50-minute annotated corpus of spontaneous speech was published in [START_REF] Obin | Comparaison de trois outils de détection semi-automatique des proéminences dans les corpus de français parlé[END_REF].

Constitution principles

The three systems share at least three principles: (i) prominence is syllabic; (ii) as prominence is a local phenomenon [START_REF] Terken | Fundamental Frequency and Perceived Prominence of accented syllables[END_REF], the context-window for identification of prosodic variations must be a constrained one; (iii) the acoustic parameters involved in prominence perception are numerous, but f0 and duration are the most important ones concerning French. Beyond these three principles, they follow different options.

Thus, among the numerous acoustic parameters involved in prominence perception, the three software programs do not focus one the same prosodic features. From this point of view, ANALOR is the least sophisticated of the three. It considers the presence of a subsequent silent pause (a silent pause being considered as a strong clue for the identification of the end of a prosodic group in French [START_REF] Lacheret-Dujour | La prosodie du français[END_REF]), and it calculates significant variations in relative height and relative duration averages to detect the syllables which stand out from their environment like a figure on a ground. PROSOPROM does the same, one difference however is that it also considers the presence of a rising tone on the current syllable (if the amplitude of the contour reaches a certain value, the syllable will be considered as prominent). IRCAMPROM is the most complex of the three tools, as the prominence detection it conducts consists in the manipulation of ten acoustic parameters, comprising duration (syllable duration, local speech rate and nucleus duration); pitch (f0), and spectral (specific loudness) features.

Concerning the context-window for relative calculations of significant prosodic variations, ANALOR employs the "prosodic period" (a unit defined by the presence of a silent pause following a contour of a certain amplitude, and associated with a melodic reset, see [START_REF] Avanzi | A Tool for Semi-Automatic Annotation of French Prosodic Structure[END_REF] for further details), i.e. it uses a more or less large dynamic unit (like any other discourse unit, the size of a "prosodic period" varies greatly from one speaker to another). PROSOPROM considers a static and constrained domain for prominence detection, namely the immediate syllabic context (the two preceding syllables and the following one), while IRCAMPROM mixes the two strategies by taking into account the immediate syllabic context (one syllable before, one after) and the inter-pausal group.

Performances

A subpart of the C-PROM database (see [START_REF] Avanzi | C-PROM. An Annotated Corpus for French Prominence Studies[END_REF] and see §3.4. below) has been used to train, evaluate and compare the three algorithms. The set of recordings (50-minutes long) was composed of a total of 12851 syllables (semi-automatically parsed with the EasyAlign [START_REF] Goldman | EasyAlign: a semi-automatic phonetic alignment tool under Praat[END_REF] Praat [START_REF] Boersma | Praat: doing phonetics by computer (Version 5.1)[END_REF] script), and annotated for prominence analysis by two experts. During the manual annotation by these two experts, 973 syllables were excluded (because they were associated with an elongation connected with a hesitance or because they presented specific prosodic properties, such as being in a post-focus position or containing a schwa, see [START_REF] Avanzi | C-PROM. An Annotated Corpus for French Prominence Studies[END_REF] for the details of the procedure) and 3244 syllables were annotated as prominent. Out of the remaining syllables, 8634 units are non-prominent and nonexcluded syllables.

Two of the software programs were automatically trained on the basis of the manual annotation. While PROSOPROM conducted a discriminant analysis, IRCAMPROM conducted both a discriminant analysis and a context-dependency to determine the best threshold for automatic prominence labeling. The results showed that the tool which had not been trained was the less robust. Indeed, ANALOR presents an fmeasure of 69.7%, with a tendency to under-detection (recall: 63.6% and precision: 77.2). PROSOPROM performs slightly better (f-measure: 71.7%), but tends to over-detection (recall: 78.9%, and precision: 68.2%) while the performance of IRCAMPROM is the highest (f-measure 75.4%) and the most well-balanced (recall: 76.4%, and precision: 74.5%).

Summary and consequences for future work

This study is interesting with regard to three points. (i) It revealed that too large a window for the relative acoustic calculation (such as the prosodic period) engenders underdetection; too small a window (such as the one PROSOPROM uses), however, is not more adequate, because it tends to overdetection. A compromise between the two seems to be the optimum solution. (ii) The comparison of the three algorithms reveals that increasing the acoustic parameters did did not lead to significant improvements in performance (when the four acoustic PROSOPROM parameters were compared with the ten IRCAMPROM features, a MacNemar test (p = 0.005) showed that there was no significant difference between the performances of these two tools). In linguistics, as elsewhere, the simpler the system, the better. We therefore decided to manipulate as few criteria as possible. (iii) The experiment was also instructive because it showed the limits in the generalization ability of a rule based system and the need for a corpus-based training for prominence detection.

Prominence detection with ANALOR

These observations have guided our improvements to the ANALOR software. In the next section, we present the changes we have made to the original algorithm as it was described in [START_REF] Avanzi | A Tool for Semi-Automatic Annotation of French Prosodic Structure[END_REF].

Acoustic parameters calculation

The automatic algorithm still relies on basic relative acoustic parameters such as f0, duration and pause. Three changes have however been made.

The first concerns the context-window for relative calculations of duration and height averages. While in the original algorithm we considered the intonational period to estimate the significant melodic and duration variations, we now use a fixed environment, determined by the three preceding syllables and the three following ones of the current syllable. This strategy was chosen in order to determine a processing window close to the accentual phrase (this unit, which is hard to define on grammatical criteria, is generally considered as composed at most of seven syllables, see [START_REF] Wiolland | Les structures rythmiques du français[END_REF] and [START_REF] Martin | Prosodic and rhythmic structures in French[END_REF]).

One other change we made concerns relative syllabic duration. Ideally, a syllable duration model based on intrinsic syllable properties and normalized local speech rate for spontaneous speech should be used (for the first experiment on read aloud sentences see [START_REF] Obin | A Multi-Level Context-Dependent Prosodic Model Applied to Durational Modeling[END_REF]). However, such a model still has to be reliably developed and tested. We therefore took only the number of phonemes of the syllable into account, thus avoiding the bias of syllable weight: for example a syllable composed of five phones is by nature longer than a monophonemic one, as has been demonstrated by work on syllabic quantities (see for example [START_REF] Dell | Generative Phonology and French Phonology[END_REF]).

The last modification made concerns rising tones. Like PROSOPROM, ANALOR now detects a syllable as prominent if it bears a rising tone reaching a certain amplitude. One difference however between the two tools is that in ANALOR, the rise amplitude is measured on the vocalic part of the syllable, not on the whole part of it. This restriction to nucleus is based on the fact that the melodic variations on consonants are less relevant perceptually than those borne by vowels [START_REF] House | Tonal Perception in Speech[END_REF]).

Figure 1 illustrates how ANALOR calculates the different acoustic parameters used for prominence detection. The algorithm calculates, for the current syllable (S 0 ), the following features: its relative height and duration average compared with the f0 and averages of the three preceding syllables (S -3 ; S -2 and S -1 ) and the three following ones S +1 ; S +2 and S +3 ), the presence of a rise if there is a positive movement of f0 on the syllabic nucleus, and the presence of an adjacent silent pause (the latter label is based on the pre-manual syllable segmentation of the corpus). F0 measures are given in semi-tones, while duration measures are calculated without any unit. Note that the contextual relativization is blocked if there is a syllable marked as excluded in the labeling tier (based on the pre-manual annotation of the corpus) or a silent pause in the immediate context of the current syllable. In the example, the last syllable of the utterance is followed by a pause. Duration and f0 measures are thus calculated only with reference to the three preceding syllabic intervals. Clicking on the current syllable makes a small window appear in which one can consult the different measures calculated.

Method for prominence threshold optimization

As mentioned in the previous section, prominence detection is performed on the basis of a multi-criteria analysis which relies on five parameters. The silent pause parameter does not need to be trained (the duration of such a prosodic object is not important in a prominence identification task, as we consider that the presence of a pause is sufficient to activate prominence, see [START_REF] Avanzi | A Tool for Semi-Automatic Annotation of French Prosodic Structure[END_REF] for the details of the argumentation), but the other four have to be. They are:

• The relative syllabic duration threshold, S D • The weight given to the number of phones in the calculation of the syllable duration W Ph • The relative syllabic height average threshold, S H • The intra-vocalic amplitude rise threshold, S R

The method we decided to follow in order to obtain the best parameters for automatic prominence identification consisted in carrying out a supervised corpus-based learning. The aim was to hone the f-measure performance by comparing systematically the results with the human annotations.

The algorithm used for automatic learning is based on a random local search, in decreasing steps, in the parameter space from a relevant value. More precisely, if V is a vector of the space (a 4-D space, the vector V having as components S D , W Ph , S H and S R ), the algorithm can be described as follows:

Let δ i be the browse step, V i the value of the parameter set, and F i the F-measure at step i of the procedure. We perform a random search to find a new value of V which improves the Fmeasure by searching in the neighborhood of V i defined by step δ i . That is to say we try the V values of the form:

i i i V V V ⋅ Φ ⋅ + = δ (1)
where Φ is a normally regular distributed random vector in the hypercube unit.

As long as we find a better value for V, we continue by replacing V i by this value. If N max attempts are made without finding a better value, we proceed to step i+1 of the procedure with a step δ i+1 = δ i /2. The procedure stops when the step becomes smaller than the ordinate given value δ min . The results given below were obtained with N max = 250, δ 1 = 0.4 and δ min = 0.01.

To conclude this description of the corpus-based learning method, it should be pointed out that this algorithm is efficient if and only if the initial values of the parameters are sufficiently close to the optimal values. In other words, the initial values were fixed on the basis of a linguistic analysis, calling on specific linguistic knowledge. For this study, we considered the following initial values: S D = 2; W Ph = 3.3; S H = 2 and S R = 3. For a justification of the value of these thresholds fixed a priori, the reader is referred to [START_REF] Lacheret-Dujour | La prosodie du français[END_REF], [START_REF] Rossi | Le seuil différentiel de durée[END_REF], [START_REF] D'alessandro | Automatic pitch contour stylization using a model of tonal perception[END_REF] and [START_REF] Garnier-Rizet | Elaboration d'un module de règles phonéticoacoustiques pour un système de synthèse à partir du texte en français[END_REF].

Material

The C-PROM corpus was used to train the algorithm and compare its performance with a manual annotation. As the corpus is fully presented in [START_REF] Avanzi | C-PROM. An Annotated Corpus for French Prominence Studies[END_REF], only a brief summary is given here. The corpus is 70 minutes long, comprises 7 genres, with, from the more to the less formal: Read Speech (RS), Political Speeches (PS), Conferences (CF), News Broadcasts (NB), Radio Interviews (RI), Map Tasks (MT) and Life Stories (LS); in all, 29 native speakers of French (13 females, 16 males) from Belgium, Switzerland and France are involved. On the basis of pre-manual syllable segmentation, two expert transcribers annotated the prominent syllables of the corpus, and labelled elongations associated with a hesitance, posttonic schwas and post-focus syllables. One of the authors of this study re-annotated post-tonic schwas and post-focus syllables as prominent or non-prominent syllables. He also excluded the syllables preceding a pause connected with a syntactic interruption, in order to filter the silent pauses. During this coding phase, he also corrected certain annotations (removed, deleted or added some syllables boundaries). Table 1 shows the detail of the corpus used for this study. It comprises 17730 syllables, among which 4676 were marked as prominent (P), 618 excluded via the manual annotation tier (Z), and 12436 which were neither associated with a hesitance or a syntactic interruption, nor were prominent (NP). The algorithm uses the 17112 valid syllables (P + NP syllables) to train itself.

Evaluation

Following the method described in §3.2., we trained, for each discourse genre, the intuitive thresholds initially fixed. The measure selected to assess agreement between the manual annotation and the automatic identification is the f-measure, that is to say the harmonic average between precision and recall [START_REF] Van Rijsbergen | Information Retrieval[END_REF]. Table 2 shows the performance of our tool for each discourse genre. As we can see, the corpus-based learning improved the results by about 3.87% of f-measure: the performance before training is 75.3%, against 79.15% after training. The best progression is for the LS discourse-genre (6%) and the worst for RS (1.57%). Concerning the agreement rate between manual annotation and automatic detection, it can be seen that the best score is for PS, while the worst is for LS recordings. Globally, the performance reached by our tool (79.15%) is close to the inter-annotator consistency found by [START_REF] Avanzi | C-PROM. An Annotated Corpus for French Prominence Studies[END_REF] (where it was estimated at 82.8% of F-measure), which is quite encouraging.

While it may be a little adventurous to compare two experiments which were not carried out with exactly with the same material, we can conclude that the modifications made considerably enhanced the detection precision of our tool. The improvement introduced also made it possible to adjust the precision and the recall, and to achieve a more well-balanced detection. When precision and recall between the two performances are compared, results show that, apart from PS and LS, the detection is sufficiently well-balanced. Moreover, in comparison with the first experiment, the final results no longer tend to over-or under-detection (recall = 78.03 and precision = 80.37).

Discussion & Conclusion

The aim of this paper was to present a software tool for semiautomatic prominence detection in spoken French. From a prealigned and annotated transcription, the ANALOR algorithm calculates the value of a certain number of prosodic contextual variations, involving f0, duration and pause features. On the basis of a manual prominence annotation, it then estimates the best thresholds associated with the activation of syllabic salience. The performances obtained on the corpus studied gave encouraging results, as they reveal that the variation between human and automate was nearly the same as the variation between two humans. Our following investigations will focus on the detection of elongation connected with a hesitance, and integrate syntactic tagging, in order to conduct a fully automatic prominence detection in spontaneous speech. ANALOR can be downloaded from: http://www.lattice.cnrs.fr/Analor.html. Sources are in free access.

Figure 1 :

 1 Figure 1: ANALOR screen shot of the utterance: "euh jusqu'à l'église Notre Dame vous prenez la première à gauche" [mp-7]. On the abscissa, temporal values are given in milliseconds; on the ordinate, the values of F0 in a logarithmic scale can be seen. Duration labels are given in milliseconds. Annotation tiers are, from top to bottom: phones, syllables (both in SAMPA), manual annotation ("prommanu", indicating prominence syllables (P), excluded syllables (z), silent pause (_) and breath (*)) and graphemic words.

Table 1 .

 1 Details of the corpus study, with, from left to right: discourse genre, duration, number of syllables,

	number of prominences (P), non-prominent/non-
	excluded syllables (NP) excluded syllables (Z), and
			valid syllables.
	Disc. genre	Duration (sec.)	Nb. Syll.	P	NP	Z	Valid_ syll.
	RS	401	1830	470	1357	0	470
	PD	635	2174	632	1539	1	633
	NB	621	3165	825	2279	58	883
	CF	687	3133	818	2202	108	926
	RI	627	2591	684	1806	90	774
	MT	590	2222	562	1490	162	724
	LS	622	2663	685	1763	199	884
	TOTA L	4183	1773 0	467 6	12436	618	17112

Table 2 .

 2 % of F-measure for each discourse genre, before and after training. Average for all the discourse genres is given in the grey columns. The column "gain" indicates the jump before and after learning.

	Genre	initial performance	trained performance	Gain
		Prec.	Rec.	F-ms	Prec.	Rec.	F-ms
	RS	79.86	71.7	75.56	76.41	77.87	77.13	1.57
	PS	75.07	83.39	79.01	82.35	81.86	82.16	3.15
	NB	74.57	73.58	74.07	75.7	82.3	78.86	4.79
	CF	76.11	73.23	74.64	79.18	79.95	79.56	4.92
	RI	71.88	82.6	76.87	79.3	80.89	80	3.13
	MT	75.31	76.51	75.9	79.86	79	79.43	3.53
	LS	83.27	61.75	70.91	73.44	80.73	76.91	6.00
	TOT.	76.58	74.68	75.28	78.03	80.37	79.15	3.87

Acknowledgments

Funding for this research was provided by two institutions: the Swiss National Science Foundation (under grants n°PBNEP1-127788 and n°100012-113726/1, Neuchâtel University), and the Agence Nationale de la Recherche (ANR-07-CORP-030-01, "Rhapsodie -Corpus prosodique de référence du français parlé"). Thanks also to B. Victorri (Lattice/ENS, Paris) for friendly help in the different stages of the ANALOR software design.