Miaojing Shi

Hervé Jégou

Early burst detection for memory-efficient image retrieval

Recent works show that image comparison based on local descriptors is corrupted by visual bursts, which tend to dominate the image similarity. The existing strategies, like power-law normalization, improve the results by discounting the contribution of visual bursts to the image similarity.

In this paper, we propose to explicitly detect the visual bursts in an image at an early stage. We compare several detection strategies jointly taking into account feature similarity and geometrical quantities. The bursty groups are merged into meta-features, which are used as input to stateof-the-art image search systems such as VLAD or the selective match kernel. Then, we show the interest of using this strategy in an asymmetrical manner, with only the database features being aggregated but not those of the query.

Extensive experiments performed on public benchmarks for visual retrieval show the benefits of our method, which achieves performance on par with the state of the art but with a significantly reduced complexity, thanks to the lower number of features fed to the indexing system.

Introduction

S ELF-SIMILARITY in images is a recurring concept in image analysis and computer vision. It is related to the statistics of natural images, which are highly redundant. This concept has been tackled in many applications. For instance, it is exploited in the non-local means de-noising algorithm [START_REF] Buades | A non-local algorithm for image denoising[END_REF], where each patch is updated by a weighted sum of similar patches. It is also useful for spatial verification and image rectification by exploiting the geometrical assumption of repeated patterns [START_REF] Pritts | Detection, rectification and segmentation of coplanar repeated patterns[END_REF]. In the context of image matching, early works [START_REF] Deselaers | Global and efficient selfsimilarity for object classification and detection[END_REF] like the one of Shechtman and Irani [START_REF] Shechtman | Matching local self-similarities across images and videos[END_REF] compute the similarity between two images with the "self-similarity descriptor", a compact local descriptor that is densely computed on the image.

In recent works based on SIFT local features [START_REF] Lowe | Distinctive image features from scale-invariant keypoints[END_REF], the underlying statistical phenomenon is often referred to as visual burstiness [START_REF] Jégou | On the burstiness of visual elements[END_REF], by analogy to the terminology used in a context of textual information retrieval. As in [START_REF] Lewis | Naive (Bayes) at forty: The independence assumption in information retrieval[END_REF][START_REF] Madsen | Modeling word burstiness using the dirichlet distribution[END_REF] where models like the Dirichlet distributions [START_REF] Madsen | Modeling word burstiness using the dirichlet distribution[END_REF] are proposed to better reflect the bursty nature of documents. Computer vision researchers question the issue of feature independence implicitly assumed in the bag-of-words model [START_REF] Jégou | On the burstiness of visual elements[END_REF][START_REF] Jégou | Aggregating local image descriptors into compact codes[END_REF][START_REF] Cinbis | Image categorization using Fisher kernels of non-iid image models[END_REF][START_REF] Revaud | Correlation-based burstiness for logo retrieval[END_REF][START_REF] Torii | Visual place recognition with repetitive structures[END_REF][START_REF] Delhumeau | Revisiting the VLAD image representation[END_REF], they show the importance of taking care of visual burstiness in image retrieval and image classification: the bursty features tend to dominate the similarity measure, which degrades the quality of the comparison, as other non-bursty yet possibly distinctive features have a comparatively lower contribution.

Various strategies have been proposed to discount the contribution of bursts on the similarity measure. Among the proposed approaches, some are inspired by text like the so-called power-law normalization [START_REF] Jégou | On the burstiness of visual elements[END_REF][START_REF] Jégou | Aggregating local image descriptors into compact codes[END_REF] for bag-ofwords or the Polya or Dirichlet models [START_REF] Cinbis | Image categorization using Fisher kernels of non-iid image models[END_REF]. These strategies have been pragmatically extended to and improved for more complex image vector representations such as VLAD [START_REF] Arandjelovic | All about VLAD[END_REF][START_REF] Delhumeau | Revisiting the VLAD image representation[END_REF] or the Fisher vector [START_REF] Perronnin | Improving the fisher kernel for large-scale image classification[END_REF][START_REF] Cinbis | Image categorization using Fisher kernels of non-iid image models[END_REF]. They are also standardly used in matching approaches like Hamming Embedding [START_REF] Jégou | Improving bag-offeatures for large scale image search[END_REF] or selective match kernels (SMK/ASMK) [START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF]. Recently, We stress a key difference between textual and visual bursts. In images, the space of features is continuous and not discrete as in text, which makes it difficult to determine which features are bursty or not. This may explain why bursts are handled by very simple techniques such as power-law, residual normalization [START_REF] Arandjelovic | All about VLAD[END_REF][START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF] or weighting votes [START_REF] Jégou | On the burstiness of visual elements[END_REF]. This paper revisits the concept of visual bursts by considering several detection strategies aiming at identifying the bursts directly from the SIFT descriptors. Our approach is inspired by the work of Turcot and Lowe [START_REF] Turcot | Better matching with fewer features: the selection of useful features in large database recognition problems[END_REF], who remove the features that are unlikely to match a query in an image collection. In contrast to their approach, which requires to off-line cross-match the whole database, we focus on detecting bursts within an image. Another difference is that we merge similar descriptors into a single representative vector instead of selecting features. Therefore we compress the representation without discarding any feature.

The effectiveness of our approach depends on two important design choices. First, we construct the affinity matrix between patches. We combine (i) a probabilistic measure learned on a patch database [START_REF] Winder | Learning local image descriptors[END_REF] with (ii) a kernel de-1 fined on geometrical quantities such as scale and orientation, which were shown useful for burst detection by Torii et al. [START_REF] Torii | Visual place recognition with repetitive structures[END_REF]. Second, we evaluate several kernelized clustering algorithms to produce groups from the affinity matrix. The clear winner amongst all clustering methods is a simple strategy performing the connected component analysis of the thresholded matrix.

Finally, we propose an asymmetric aggregation method: we apply our burst detection method on database side but do not aggregate the query descriptors. This further improves the performance while offering a memory footprint per image identical to the one of our symmetric burst aggregation.

The paper is organized as follows. Section 2 introduces our representation and retrieval model. Section 3 discusses the concept of visual burst and proposes our method to detect bursts. Section 4 evaluates our methods on public retrieval benchmarks. Our results demonstrate the benefits of our approach, which improves the state-of-the-art in memory/performance trade-off.

Representation and matching

We assume an image is represented by a set F of local features, where each feature f ∈ F is represented by a d-dimensional local descriptor u f , local scale s f and orientation θ f . We ignore position because we do not use geometrical information to match two images, but rather to analyze similarities within images. We further assume that each descriptor x = u f is quantized on a codebook C of k visual words, or cells. We adopt the matching model [START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF], whereby the similarity of images F, G is measured by

S(X , Y) = ν(X )ν(Y) c∈C w c M(X c , Y c ), (1)
where X , Y are the descriptors of F, G respectively, X c are the descriptors of X assigned to cell c, M is a cell similarity function, w c is a weighting factor for c and ν(X ) is a normalization factor such that self-similarity of X is S(X , X ) = 1. Although ( 1) is a general model that includes special cases of several popular methods like bag of words (BoW) [START_REF] Sivic | Video Google: A text retrieval approach to object matching in videos[END_REF], VLAD [START_REF] Jégou | Aggregating local image descriptors into compact codes[END_REF] and Hamming Embedding (HE) [START_REF] Jégou | Hamming embedding and weak geometric consistency for large scale image search[END_REF], it is clearly motivated by discarding geometric information for efficiency reasons. We would rather like to detect burstiness at an early stage to fuse them, and to use any standard search infrastructure off-the-shelf. Therefore, given an image F, we detect feature bursts in F and represent it by a set of aggregated descriptors. This is an off-line operation, i.e., the descriptors can be quantized, encoded and searched as usual.

For the cell similarity function M, we use VLAD [START_REF] Jégou | Aggregating local image descriptors into compact codes[END_REF][START_REF] Jégou | Aggregating local image descriptors into compact codes[END_REF] and SMK/ASMK [START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF]. These are two methods targeted for different scenarios with different memory/speed/accuracy compromises. Our descriptor aggregation can be combined After PCA analysis, we plot two of the principal components found (component 6 vs. 12). Colored groups of points correspond to the six most populated bursts, exactly as in Fig. 1. Gray points correspond to smaller bursts. Smaller light gray dots are isolated descriptors that do not belong to any burst.

and provide benefits in both frameworks. Interestingly, the state-of-the-art ASMK, which is also an aggregated representation intended to address the burstiness problem, is complementary to our strategy.

Early detection of visual bursts

What are bursts? As a representative example, Fig. 1 depicts a clean view of a building exhibiting a lattice structure of almost identical tiles formed by its windows. To visualize the resulting groups of similar patches, we extract normalized RootSIFT [START_REF] Arandjelovic | Three things everyone should know to improve object retrieval[END_REF] descriptors on Hessian-affine [START_REF] Mikolajczyk | Scale & affine invariant interest point detectors[END_REF] features, compute pairwise distances, and find the connected components formed by joining pairs whose distance is be-low a certain threshold. This is a simple but very effective approach. By coloring features according to their group, it is clearly seen that the same pattern of 5-6 groups appears around every window on the building surface.

Since patches are very similar in appearance, one might expect a high density of points around each burst in the descriptor space, so that bursts can be easily found by clustering or mode seeking. However, as illustrated in Fig. 2, this is far from being true. It is not easy to visualize what happens in a 128-dimensional space by a mere 2D projection. Still, whatever the projection, isolated descriptors (not belonging to any group) appear to have the same density as bursty ones (belonging to some group), while bursts have arbitrary shape and large extent. One cannot hope that bursts will fit within the cells of a codebook, especially if the the latter is trained on random samples without taking burstiness into account. Our approach to detect bursts before quantizing descriptors then makes sense.

Besides structure in man-made scenes, other sources of burstiness may be texture, e.g. in natural environments, or the fact that feature detectors may give multiple responses, e.g. along edges or around corners at different scales. Depending on the case, geometry also plays a role. In contrast to methods that focus on repeating structures and symmetries [START_REF] Torii | Visual place recognition with repetitive structures[END_REF][START_REF] Tolias | Symcity: Feature selection by symmetry for large scale image retrieval[END_REF], we consider individual features disregarding position and neighborhood: the search for repeating groups of features is too constrained and may fail to identify bursts, especially in natural scenes. However, we do investigate scale and orientation. For instance, similar patches in Fig. 1 have the same orientation, but this is not always the case on a textured surface. It is not known whether bursty features share the same appearance only or scale and orientation as well; this is something we determine experimentally.

Section 3.1 defines a feature kernel measuring the similarity of two individual features. Then in section 3.2 we consider a number of methods to detect bursts using the given kernel function and conduct a preliminary evaluation.

Feature kernel

Given two local features f, g in an image, we define a feature kernel function

k(f, g) = k u (u f , u g )k s (s f , s g )k θ (θ f , θ g ), (2)
consisting of three factors, namely the descriptor kernel k u , the scale kernel k s and the orientation kernel k θ . Intuitively, this function measures if the two corresponding patches in the image are similar in appearance and have similar scales and orientations. Factors k s , k θ can be optionally omitted.

Descriptor kernel. Given a pair of descriptors x, y ∈ R d , descriptor kernel k u measures their similarity and is a function of the inner product z = x, y , which is equivalent to their distance if x, y are 2 -normalized. Seeing z as a random variable, we define this function as the probability, given z, that x, y belong to the same burst, i.e. they correspond to two matching image patches. In particular, we adopt a generative model for a binary classifier: if B is the class of descriptor pairs that belong to the same burst and B is its complement, we define

k u (x, y) = p(B| x, y ), (3)
where

p(B|z) = p(z|B)p(B) p(z|B)p(B) + p(z|B)p(B) (4)
is the posterior probability of B given z; p(z|B), p(z|B) are the class-conditional densities of B, B respectively and p(B), p(B) are their prior probabilities. We train such a classifier from a dataset of matching/non-matching patch pairs [START_REF] Winder | Picking the best daisy[END_REF]. This dataset consists of patches sampled from 3D reconstructions of the Statue of Liberty (New York), Notre Dame (Paris) and Half Dome (Yosemite). Two patches in two different views of the same 3D scene are matched if they are projections of the same 3D point. Such patches are very similar in appearance, so they provide a good model for bursts.

We extract a SIFT descriptor from each patch in the dataset and compute the inner product z = x, y for each pair (x, y) of descriptors. If B, B are the sets of all observations of z for matching and non-matching pairs respectively according to the ground truth, we model the classconditional densities p(z|B), p(z|B) by fitting normal densities to the samples of B, B respectively, according to maximum likelihood. The prior probabilities are p(B) = |B|/N, p(B) = |B|/N , where N = |B| + |B| is the total number of samples. Fig. 3 shows the posterior probability p(B|z) computed from (4). It appears that k u (x, y) is a sigmoid function of the inner product z = x, y that can discriminate well enough matching from non-matching descriptor pairs. Scale and orientation kernels. Given two patch scales s, t, scale kernel k s (s, t) is given by a Gaussian kernel of their logarithms,

k s (s, t) = exp -λ log 2 s t . (5)
This choice makes k s invariant to absolute scale, as long as ratio s/t remains constant. The situation is similar for orientation, but following the work [START_REF] Tolias | Orientation covariant aggregation of local descriptors with embeddings[END_REF], we use the equivalent of Gaussian for periodic distributions, which is the von Mises distribution. In particular, given two patch orientations θ, φ, orientation kernel k θ (θ, φ) is given by the von Mises kernel

k θ (θ, φ) = exp(κ cos(θ -φ)) -exp(-κ) 2 sinh(κ) . (6)
Parameters λ, κ are tuned experimentally according to [START_REF] Tolias | Orientation covariant aggregation of local descriptors with embeddings[END_REF].

Burst detection and aggregation

Given an image F = {f 1 , . . . , f n } with n features, define n × n affinity matrix K with elements

K ij = k(f i , f j ) (7)
for i, j = 1, . . . , n, where kernel k is given by ( 2). The affinity matrix includes all pairwise feature similarities in F and is the only input for burst detection. Now, given the discussion so far, a candidate algorithm should

• be based on a kernel method, or more generally, operate on metric spaces. One reason is that bursts are of arbitrary shape in the feature space, as shown in Fig. 2. Another is that we have formulated the input as an affinity matrix, in order to combine with scale and orientation proximity. This excludes algorithms that represent points in a Euclidean space, like k-means.

• be able to automatically determine the number of groups such that non-matching features are never grouped, or at least have a parameter to control it so that the resulting number varies smoothly and can be close to the original size n. This is because we would like the number of aggregated descriptors to vary from n down to a certain percentage of n.

Since we look for groups of similar features as measured by kernel k, any clustering or mode seeking algorithm that respects the above constraints would do in theory. Thus we examine a number of existing methods.

Connected components. Features are treated as nodes of an undirected graph with an edge for each pair (f, g) of features with k(f, g) above a threshold τ . Then we compute the connected components of the graph and consider each component with more than one feature to be a bursty group.

The remaining components each contain one isolated feature. This is the fastest and most effective method.

Quick shift [START_REF] Vedaldi | Quick shift and kernel methods for mode seeking[END_REF] is a very simple, fast mode seeking method that can operate in non-Euclidean spaces. Eventually, all points are connected into a single tree; after that, edges are disconnected according to a threshold τ . This aspect is similar to connected components: τ needs to be tuned to obtain the desired number of groups, but we evaluate a range of values in our experiments anyway.

Kernel k-means [START_REF] Schölkopf | Nonlinear component analysis as a kernel eigenvalue problem[END_REF] is a simple kernel method, parametrized by the desired number k of groups. However, it has high complexity and is not designed for k being large.

Spectral methods. Representative spectral methods include spectral clustering [START_REF] Ng | On spectral clustering: Analysis and an algorithm[END_REF] and normalized cuts [START_REF] Shi | Normalized cuts and image segmentation[END_REF][START_REF] Fowlkes | Spectral grouping using the Nyström method[END_REF]. Certain group of bursty features is expected to contribute most of its energy to one of the leading eigenvectors of matrix K and give the largest projection on this eigenvector. It is possible to specify the number of groups -e.g., apply k-means on those leading eigenvectors [START_REF] Ng | On spectral clustering: Analysis and an algorithm[END_REF]. But the cost is prohibitive in general. We design a method which hierarchically applies spectral clustering to subdivide each group, while automatically determining the number of groups. We call this variant hierarchical spectral clustering.

Evaluation. We conduct a preliminary qualitative evaluation of the above methods on a limited sample of images to determine whether they indeed satisfy our constraints and make an initial selection before moving on to larger scale quantitative experiments. We present here an example on one representative image as shown in Fig. 4.

We have tuned each method such that the number of detected groups is 80-85% of the initial features; since all descriptors in a group are aggregated, this measure is referred as aggregation% in the experiments and is crucial in the memory-performance trade-off. It can be seen that most methods yield consistent groups; however, normalized cuts gives many inconsistent groups while the groups found by spectral clustering are too small. The result of connected components is the cleanest, and Fig. 6 verifies this fact: each group contains almost identical patches, precisely centered at the position of each feature.

Fig. 5 further shows the group size distributions. It appears that kernel k-means is problematic in the sense that the groups found are far less than the target, resulting in an aggregation% of 39%, rather than 80%. Although the required number of groups is given as a parameter, too many clusters become empty and the few remaining are most detected as bursts. Spectral clustering finds too many small groups. In general, we would like most features to remain isolated and the remaining ones form few bursts. In this sense, connected components, hierarchical spectral clustering and normalized cuts appear reasonable. Taking into account the preliminary evaluation and the fact that the spectral methods are quite slow to apply at large scale, we choose the first three methods of Fig. 4 for further quantitative evaluation in the context of retrieval.

Burst aggregation. Given an image, the result of burst detection is a partition of its features into groups. We simply take the average of the descriptors in each group and 2normalize them. Discarding geometry, this yields a set of (aggregated) descriptors to represent the image, so any encoding or search model applies.

Experiments

We evaluate and compare the proposed burst detection and aggregation in the context of two different image retrieval models, namely VLAD and SMK/ASMK. We first discuss the evaluation protocol and give some implementation details; then we discuss the impact of parameters for each method and analyze the benefits we obtain in the memory-performance trade-off.

Experimental setup

Datasets. We conduct experiments on three retrieval benchmarks, namely Holidays [START_REF] Jégou | Hamming embedding and weak geometric consistency for large scale image search[END_REF], Oxford [START_REF] Philbin | Object retrieval with large vocabularies and fast spatial matching[END_REF], and Paris [START_REF] Philbin | Lost in quantization: Improving particular object retrieval in large scale image databases[END_REF]. We study the impact of parameters mainly on Holidays. To evaluate performance on larger scale, we add distractors from the Flickr 100k set [START_REF] Philbin | Object retrieval with large vocabularies and fast spatial matching[END_REF] to Holidays and Oxford.

Descriptors. Local features are extracted with the Hessianaffine detector [START_REF] Mikolajczyk | Scale & affine invariant interest point detectors[END_REF] on Holidays and its improved version [START_REF] Perdoch | Efficient representation of local geometry for large scale object retrieval[END_REF] on Oxford and Paris. We adopt the default parameters of the detector, but we also use a lower threshold and larger patch size to yield different feature sets for Holidays. Since we are generating a reduced feature set by aggregating, this helps evaluate the performance at the same memory depending on the initial feature set. the three different feature sets used. We use RootSIFT [START_REF] Arandjelovic | Three things everyone should know to improve object retrieval[END_REF] descriptors in all our experiments.

Evaluation. Retrieval performance is measured in terms of mean average precision (mAP). As we vary the number of detected bursts, we generate aggregated feature sets of varying size; the ratio to the original size, averaged over a dataset, is called aggregation%. We thus measure mAP as a function of aggregation% to evaluate the memoryperformance trade-off. When an inverted file is used, we also measure the imbalance factor [START_REF] Tavenard | Balancing clusters to reduce response time variability in large scale image search[END_REF], which is directly related to the search cost and should be as close as possible to the optimal value of 1.

Burst detection and aggregation. On Holidays, we employ the proposed descriptor kernel and scale kernel only; referring to (2), we use kernel k u k s . On Oxford and Paris on the other hand, we use all three kernels, i.e. descriptor, scale and orientation; that is, k u k s k θ . This setting always gives the best performance. We initially evaluate three different burst detection methods, and then focus on connected components. We apply different thresholds to the affinity matrix to vary the number of bursts such that aggregation% varies in the range of 10-100%. In all graphs, the baseline is always the rightmost point. We follow two strategies: database descriptors are always aggregated, while query descriptors may be aggregated or not; these are called symmetric and asymmetric aggregation, respectively.

Retrieval models. We conduct experiments on two representative retrieval models, VLAD [START_REF] Jégou | Aggregating local image descriptors into compact codes[END_REF] and SMK/ASMK [START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF]. In particular, we use the efficient versions SMK*/ASMK* where descriptors are binarized.

Both models target at reducing the effect of burstiness: VLAD by power-law normalization, and ASMK by its own aggregation after quantization. We present the benefit from our early burst detection but interestingly we also show it can be complementary to such methods.

Cost. The query cost is quadratic (linear) in aggregation% for symmetric (asymmetric) aggregation, i.e. always less than baseline. The off-line additional cost of burst detection and aggregation is O(n 2 ) where n is the number of features per image. As a comparison, quantization with a flat vocabulary is O(nk), where k is the vocabulary size. Therefore the fixed cost of early detection is negligible in the AMSK pipeline (k n) and more expensive for VLAD (k < n), yet reasonable. . Size distribution of groups found by each method for the example of Fig. 4. Groups of two features or more are considered bursts and the remaining groups each contain one isolated feature. Observe the logarithmic axis: bursts are only a small fraction of groups.

Results on VLAD

Burst detection and aggregation. Fig. 7 illustrates the performance of VLAD on Holidays-L under varying aggrega-tion%. As discussed in Section 3.2, we compare the three most promising methods of the initial qualitative evaluation, i.e. connected components, quick shift and hierarchical spectral clustering. Connected components choice is always superior, while the other two methods do not achieve any benefit. Therefore, we focus all remaining experiments on connected components.

Large-scale. strategy for the remaining results. This behavior can be explained by the fact that under severe aggregation on both images, most matches are lost. We also observe an impressive improvement on the memory-performance tradeoff: we can keep only 30% of the original descriptors for a performance drop of merely 1%.

Initial features. Fig. 9 compares three different initial feature sets on Holidays and measures mAP vs. absolute number of descriptors/image, which directly reflects memory. Now comparing the three sets for any number of descriptors, the largest set maintains a gain of over 10% over the smallest one. This is another aspect of the trade-off and suggests a way to improve performance: augment the initial features, aggregate, and gain in mAP at the same memory.

Imbalance factor. Fig. 10 and11 investigate the imbalance factor [START_REF] Tavenard | Balancing clusters to reduce response time variability in large scale image search[END_REF] on Holidays-L, Oxford and Paris. By aggregating bursty features at an early stage, we make the inverted file more balanced. Interestingly, the imbalance factor exhibits a minimum at an aggregation% which gives at the same time a good memory-performance trade-off, e.g. 60%, 30% respectively for SMK*/ASMK* on Holidays-L.

In terms of query cost, the benefit of improved imbalance factor should be multiplied by the benefit due to decreased memory: indeed, query time is linear in aggregation%.

Large scale. Table 3 shows large scale results on Holidays-L and Oxford plus distractors. It is interesting that e.g. in Oxford, the result is more promising than at small scale: we can save 15% of memory at no performance cost and increase efficiency at the same time.

Comparison to the state of the art. Table 4 shows stateof-the-art results compared to our best results on ASMK*. We only compare to methods relating to vocabularies and descriptor representation and not e.g. spatial matching [START_REF] Perdoch | Efficient representation of local geometry for large scale object retrieval[END_REF][START_REF] Avrithis | Hough pyramid matching: Speeded-up geometry re-ranking for large scale image retrieval[END_REF], query expansion [START_REF] Chum | Total recall II: Query expansion revisited[END_REF][START_REF] Tolias | Visual query expansion with or without geometry: refining local descriptors by feature aggregation[END_REF], feature augmentation [START_REF] Turcot | Better matching with fewer features: the selection of useful features in large database recognition problems[END_REF][START_REF] Arandjelovic | Three things everyone should know to improve object retrieval[END_REF] or nearest neighbor re-ranking [START_REF] Qin | Hello neighbor: Accurate object retrieval with k-reciprocal nearest neighbors[END_REF]. The first group of methods relies on a large vocabulary (1M or more) and does not include a descriptor signature. Performance may be improved by learning a finer vocabulary on a larger training set [START_REF] Mikulik | Learning a fine vocabulary[END_REF], which is a costly off-line process, or using the extremely fine partition of a multiindex [START_REF] Avrithis | Quantize and conquer: A dimensionalityrecursive solution to clustering, vector quantization, and image retrieval[END_REF][START_REF] Babenko | The inverted multi-index[END_REF], which cannot be fully inverted. The second group relies on a smaller vocabulary (100k or less) and embeds a descriptor signature, e.g. a Hamming code [START_REF] Jain | Asymmetric hamming embedding[END_REF][START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF] as in this work, or product quantization code [START_REF] Qin | Query adaptive similarity for large scale object retrieval[END_REF][START_REF] Jégou | Product quantization for nearest neighbor search[END_REF]. This approach is superior, but requires additional space.

The third group includes ASMK* [START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF] and this work. There is still a descriptor signature, but the number of descriptors is reduced, as indicated by aggregation%, which is different for each dataset. Despite the lower memory and faster query, these methods are superior to previous ones. Additionally, we get a performance gain over [START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF] using multiple assignment; in particular, the five nearest visual words as used in [START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF]. In Holidays, we start from the larger feature set Holidays-L and aggregate such that the total number of features is not higher than in [START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF], as in Fig. 9. In the remaining datasets, the gain is due to absolute improvement in the default feature set.

Conclusion

Handling burstiness has a significant and positive impact on the accuracy of image search comparison. This paper has shown that our early detection of visual bursts as an effective strategy to produce image match kernel based on local descriptors. It is applied prior to the indexing stage, which might separate bursty features if quantization is em- --55.8 Fine vocab. [START_REF] Mikulik | Learning a fine vocabulary[END_REF] 74.9 74.9 74.2 Multi-index [START_REF] Avrithis | Quantize and conquer: A dimensionalityrecursive solution to clustering, vector quantization, and image retrieval[END_REF] -69.6 70.3 HE [START_REF] Jégou | Improving bag-offeatures for large scale image search[END_REF] 74.5 -51.7 HE [START_REF] Jégou | Improving bag-offeatures for large scale image search[END_REF] 77.5 -56.1 AHE+burst [START_REF] Jain | Asymmetric hamming embedding[END_REF] 79.4 -66.0 AHE+burst [START_REF] Jain | Asymmetric hamming embedding[END_REF] 81.9 -69.8 Query ad. [START_REF] Qin | Query adaptive similarity for large scale object retrieval[END_REF] 81.4 70.3 73.9 Query ad. [START_REF] Qin | Query adaptive similarity for large scale object retrieval[END_REF] 82.1 73.6 78.0 aggregation% 78% 86% 89% ASMK* [START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF] 80.0 74.4 76.4 ASMK* [START_REF] Tolias | To aggregate or not to aggregate: Selective match kernels for image search[END_REF] 81.0 77.0 80. ployed, and exploits geometrical quantities jointly with feature similarity. Not only our strategy is as or more effective than other methods for handling visual bursts, but it is also complementary to concurrent like the ASMK search engine, leading to state-of-the-art results in a comparable setup.

Another key advantage is that, by fusing the descriptors before feeding them to the indexing or search system, we reduce the computational cost in both the quantization and retrieval steps, typically by a factor of two. Our method also reduces the memory footprint in the same proportion for image search engines employing an inverted file.

Figure 1 .Figure 2 .

 12 Figure 1. An image along with the features of the six most populated bursts detected. A dot is shown at the position of each feature, colored according to the burst it belongs to; the remaining features are not shown.

Figure 3 .

 3 Figure3. Distributions of z = x, y for matching and nonmatching SIFT descriptor pairs (x, y) from the dataset of[START_REF] Winder | Picking the best daisy[END_REF], where we fit class-conditional densities p(z|B), p(z|B). Posterior probability p(B|z) is used to compute kernel ku (3).

Figure 6 .

 6 Figure 6. The six most populated bursts found by connected components on the example of Fig. 4. An image patche of size 30 × 30 pixels is shown for each feature; a dot is shown at each feature position, colored according to burst exactly as in Fig. 4.

Figure 4 .

 4 Figure 4. Feature grouping and burst detection with six methods. In each case, the six most populated bursts are shown with a dot at the position of each feature, colored according to the burst it belongs to.

Figure 7 .

 7 Figure 7. VLAD performance vs. aggregation% on Holidays-L for three burst detection methods. Vocabulary size k = 16; baseline power law parameter α = 1.

= 3 5 Figure 9 .

 359 Figure 9. ASMK* performance vs. average number of aggregated descriptors per image on Holidays for three different initial feature sets and different values of selectivity exponent α. Vocabulary size k = 65k; asymmetric aggregation. Note that the rightmost measurement corresponds to aggregation% less than 1.

Figure 11 .

 11 Figure 11. SMK*/ASMK* imbalance factor vs. aggregation% on Oxford and Paris. Vocabulary size k = 65k; selectivity exponent α = 3.

Table 1 shows

 1

	feature set	#features threshold patch size
	Holidays-S	4.4M	500	21
	Holidays-M	4.3M	500	41
	Holidays-L	6.6M	300	41

Table 1 .

 1 Three feature sets obtained from Holidays with different detector parameters. Holidays-S is the default.

Table 2 .

 2 Table 2 shows large scale results on Holidays-L plus distractors. Recall that aggregation% of 1 refers to the baseline. It is impressive that we get absolute performance gain at reduced memory and query time. VLAD mAP performance vs. aggregation% on Holidays-L +Flickr 100k distractors for two vocabulary sizes, 16 and 64.

	aggregation%	1.000 0.764 0.638 0.556
	k = 16	41.3	42.7	44.1	45.0
	k = 64	46.3	47.5	48.3	48.8
	4.3. Results on SMK*/ASMK*
	Symmetric vs. asymmetric. Fig. 8 compares symmetric and asymmetric aggregation on Holidays-L; recall that in the latter case the query is not aggregated. It turns out that for low aggregation% asymmetric is superior, and this ob-servation holds for all our experiments, so we limit to this

Table 3 .

 3 ASMK* mAP performance on Holidays-L and Oxford plus Flickr 100k distractors. Vocabulary size: 65k. The first column of each dataset is the baseline.

		85
	mAP	80			SMK*, symmetric
					ASMK*, symmetric
					SMK*, asymmetric
		75			ASMK*, asymmetric
		0.2	0.4	0.6	0.8	1
				aggregation%
	Figure 8. SMK*/ASMK* performance vs. aggregation% on
	Holidays-L for symmetric and asymmetric aggregation. Vocab-
	ulary size k = 65k; selectivity exponent α = 3.
		dataset	Holidays-L 101k	Oxford 105k
	aggregation%	0.65 0.52 0.28	0.90 0.76 0.55
		mAP	85.1 84.5 77.6	68.9 68.9 63.6

Table 4 .

 4 Comparison of our best mAP result to state-of-the-art using inverted files as in BoW or also local descriptors as in HE. We only report results without spatial re-ranking.

	4

Acknowledgements. This work was supported by ERC grant VIAMASS no. 336054. Miaojing Shi was partially supported by NBRPC 2011CB302400, NSFC 61121002, 61375026 and JCYJ 20120614152136201, and Yannis Avrithis was supported by the EU (European Social Fund) and Greek National Fund through the operational program "Education and Lifelong Learning" of the National Strategic Reference Framework, research funding program "ARISTEIA", project "ESPRESSO".


HENRI TOMASI AND RADIO: A PROTEAN MUSICIAN ON THE WAVES by Christophe BENNET

Between the ages of 30 and 45, i.e. at the beginning of his musical maturity, Henri Tomasi devoted his professional life to radio. A written version of a paper proposed at the "Henri Tomasi et la Méditerranée" (Henri Tomasi and the Mediterranean) symposium held in Marseille in September 2013, this article will notably show that his position as orchestra conductor and musical manageratn Radio-Colonial, then at Radio-Paris, was a genuine "springboard" for the composer. The gathering of a wide sampling of musical programs and broadcasting press articles of the thirties enables us to highlight an unknown aspect of this musician, especially in his relation with the emerging media. At first, we are going to see how this experience already underlines his humanist involvement by confronting the expression of his conceptions of the medium with the way his work was welcomed by the broadcasting protagonists. Secondly, the eclecticism of his production and his opening to exoticism are going to be verified through Tomasi's different appearances on the waves, either as a composer or as a conductor. Finally, a survey of his very diverse broadcasted works is going to show how the medium reinforced his quality of "protean musician", posted at a crossroad of numerous and complementary aesthetics.

Throughout the thirties, at the time when radio became a mass medium in France, the broadcasting of music was absorbing 60% of the whole programs1 . During the decade, while the medium was becoming more professional, its audience figures kept increasing. Though it only concerned a few thousands middle-class people or technicians at the dawn of the thirties2 , one Frenchman out of two was having access to the "magic waves" by the time of the Second World War3 . At national and stations' levels, managers were recruiting some of the greatest personalities of the artistic area, including well-established composers. Henri Tomasi himself started his broadcasting experience in January 1931 with the creation of "Poste Colonial" (1931-1935), a government station broadcasting on short waves that was created by Marshal Lyautey and inaugurated on May 6 th 1931 within the frame of the Colonial Exhibition. A former broadcasting reporter with a long equatorial experience, Julien Maigret was the first manager. Beside the programs dedicated to the French expats in Asia, Africa and South America, he followed a quality policy as regards the other two other components of the programs: concerts and theatre, both broadcasted on a weekly basis. Conducted by Tomasi, the musical band of the station consisted of 35 musicians, but remained flexible, from a quintet to the whole orchestra. In 1934, he was appointed by Georges Colin to Radio-Paris, where, until 1939, he was to conduct many concerts and for which he wrote more than thirty pieces. Therefore, it's not astonishing to find traces of his statements about a medium that was then still emerging, and also testimonies of his action 4 .

I -HENRI TOMASI AND THE RADIO OF THE THIRTIES

In the broadcasting press of the time 5 , one can actually find many traces of his presence in the stations, and also see that the prerogatives of a "station musician" sometimes went beyond his role of conductor. Those testimonies of the daily life of the stations prove Tomasi's entire involvement

AN INVOLVEMENT CORRESPONDING TO HIS CONVICTIONS

Obviously, we are going to describe Henri Tomasi's action as a conductor and a composer, but we can right away notice that he also collaborated to "causeries musicales" (musical lectures), a program format that was very popular during the thirties. Inspired by the "Comité de propagande pour la rénovation et le développement de la musique", and broadcasted from the very beginning of the thirties on Radio-Paris, the "Causeries avec audition de disques" were a genuine model of the genre. Every week, with no fee to expect, celebrities would come to the studio and speak, bringing their knowledge "to the audience" by summarizing an issue and presenting it in a simple way. Among those lecturers one can find many composers: Louis Aubert, Pierre-Octave Ferroud, Jean Roger-Ducasse, Gustave Samazeuilh, Emile Vuillermoz, Stan Golestan, Maurice Emmanuel, and many others. While listening to those moving and rare sound archives 6 , one realizes that, independently of the proposed subject, the natural and ease in the articulation of the lecturers probably determined their audience's interest. In the matter of broadcasting, some great composers had a genuine narrative gift. In September 1936, when Henri Tomais was hosting a program of Corsican folklore on Radio-Paris, the "listening notes" of the weekly "Choisir" were using glowing terms: "Henri Tomasi, who was known as an excellent composer and orchestra conductor, hadn't told us that he also was a perfect narrator. His explanation suited every work performed by Miss Angelici perfectly well. By devoting a big part of the programs to classical music, the artistic departments of French stations were already welcoming well-known composers to let them express the multiple aspects of their art and knowledge. Beside giving them access to the microphone, their status as musicians also brought them backstage. Apart from the didactic programs that we mentioned earlier, a genre prevails during the whole decade: the vocal and instrumental recital. Born in the very first hours of the medium (owing to the difficulty to capture the sound of a band), the principle of a solo or a duet of fifteen minutes at the microphone finds its peak on Radio-Paris as early as 1936: anonymous artists perform short sequences of instrumental or vocal recital. On April 20 th 1934, the daily Comoedia already stated: "In the Paris area, two broadcasting juries have been set up. The first one, constituted by Mssrs. Inghelbrecht, Tomasi, and Jacques de la Presle, will be listening to singing or playing in front of the microphone of the government stations of the capital. 8 " Désiré-Emile Inghelbrecht's presence newt to Henri Tomasi's is not surprising. The founder of the very young Orchestre National (born in 1933), was entrusted by Minister Jean Mistler with nothing less than "the monitoring of the programs of Paris-PTT, with a right of inspection of Radio-Paris, and also the artistic management of federal programs. 9 " As for composer Jacques de la Presle, whose works were then often broadcasted on waves, he had been the artistic manager of Radio-Paris for many years. 10 Obviously, Tomasi's action as a musician devoted to a Radio in its youth is not an exceptional case. At the very beginning of the thirties, Henri Büsser was appointed manager of the musical programs of Radio-Paris; Victor Charpentier, who was the artistic manager of the first hours, was entrusted in 1933 with the artistic management of Paris-PTT, and also the role of deputy chairman of the Board of the General Society of the TSF listeners; Gustave Charpentier succeeded Paul Dukas in 1935 as member of the literary and artistic section of "Conseil Supérieur de la radiodiffusion" and Louis Aubert sat from 1927 onward on the Board of the Programs of Radio-Paris (a great private station bought by the Government in 1933).

Through their multiple responsibilities at the helm of the artistic departments of the stations, these musical protagonists were choice observers. They played an important role in the arguments about the stakes of the developing medium. Initiated by mediators (the columnists of the specialized press), these debates around the broadcasting of the thirties are fueled by the emitters, on the one hand, and the audience, on the other hand. A pessimistic view of a massive demand combined with a dwindling of sophisticated programs (educativeoriented) of the first hours especially opposed some of the programs makers. Besides, those who were denying the victory of a subculture upon a legitimate culture also refuted the 8 The second jury concerned dramatic art. 9 TSF Programmes n°202 of July 29 th 1934, p. 45 "Quelques instants avec D.-E. Inghelbrecht" by Pierre Keszler. 10 Composer Jacques de la Presle was the artistic manager of Radio-Paris as of 1930, then as of until 1943, and "Inspecteur principal de l'enseignement musical" from 1945 to 1952. A composer of symphonic pieces, he is mainly recognized for his numerous melodies, always written in a meticulous and delicate style. His famous song Chanson intime, ten times mentioned in our computation, is often present in the concerts of "light and varied symphonic music". One can see his whole catalogue at: http://www.musimem.com/La_Presle.htm (consultation of July 2013).

presumed fall of the "musical propaganda" of the programs makers11 . As for Tomasi, backed by his experience of several years at the "musical commands" of various Paris stations, he seems to have joined the category of the optimists. In 1938, he pleasantly recalls the musical awakening which the radio provided to people of a modest condition. Expressing himself in a survey called "radio et culture12 " led by Pierre Descaves for Radio-Magazine¸ he describes an example of a successful cultural penetration: "Radio is inseparable from the spreading of the appetite for culture. The mind of the new generations will be more and more curious. For example: in an old Corsican village, where I very often spend my holidays, a young shepherd last summer sang the first eight bars of the Andante of the Fifth Symphony for me. Before the radio, Beethoven was an obscure celebrity for him. You may draw the conclusion yourself!13 " Several factors may explain why the young shepherd (with folkloric references) was capable of memorizing the melody of the second movement, despite its rather sophisticated harmony14 : the readability of the melody by cellos, and probably a repeated listening of the work. One can assume that the recurrence of famous pieces stimulates the awakening of a listener to a foreign culture, without any deliberate purpose.

As we saw in the case of Tomasi, whenever composers give guidelines to the listeners, the magic seems to be there. In 1938, one of the columnists of the weekly Radio-Magazine underlined the savoir-faire of the composer of Ciboulette: "Last year, Reynaldo Hahn one evening explained 'L'Enlèvement au Sérail' with records. For someone like Reynaldo Hahn, who embodies taste, knowledge, civilization in all its shapes, how many miserable oafs and sinister drags have been speaking in front of the microphone without ever leaving it.15 " We can also notice that during the second half of the decade, a long series of 91 talks on "Le Théâtre lyrique en France depuis les origines à nos jours" comes and completes the list of the "conférences sur la musique" that Radio-Paris usually proposes to its listeners. During one of those, Henri Tomasi, then well known by the listeners, is presented as a composer.

A MUSICIAN WELL KNOWN BY THE LISTENERS

On Wednesday June 2 nd 1938, composer Louis Aubert takes part in this broadcasting series on a topic entitled: "Bondeville, Delannoy, Tomasi, Ferroud." After Emannuel Bondeville's presentation, Louis Aubert announces, in a tone that we would consider oldfashioned today: " Now, this is 'l'air de la Vieillesse', from L'École des maris performed by M. Lovano. Then, performed by M. Cathelat, a tune of the second act of L'École des maris : Comme des fleurs . 16 " He then proceeds with Henri Tomasi's presentation, then aged 37. The lectures were published, which provides an interesting occasion to assess the already well established reputation of the composer. One can see that his Mediterranean temperament is already well underlined and that the most significant features of his style are already mentioned at that time of his beginning maturity, as well as his themes of inspiration, which his future productions vouchsafed.

"After Marcel Delannoy, a musician from "Ilede-France" (the Paris area), here is a genuine Mediterranean. Born in Marseille in 1901, Henri Tomasi is of pure Corsican stock, and all his work appears to be deeply filled with this ethnical influence. This doesn't mean that we immediately pick out the great dramatic themes or the folkloric elements that are dear to his original island, as is the case for most Spanish composers for instance. Tomasi only dealt with Corsican themes in some of his works, and particularly in his Vocero, an impressive "poème symphonique", whose success was immediate and considerable.

Besides, he tried the most diverse styles and genres, and his wandering muse has made him walk about f into time and space or a long time, from ancient Greece to the Paris of the "Grands Boulevards" in 1830, to the present-day little French village to the black communities of the African Bush, then to the Far East, in the Japanese geishas' flowered gardens, after a stopover in Laos.

Yet, if I said earlier that Tomasi's music owed much to his Corsican roots, this is because I see in them the very principle of the capability (astonishingly developed in his case) to integrate everything which, under any longitude or latitude of our globe, is directly based on our popular soul. Tomasi indeed hardly borrows from the folklore of the diverse countries that he is inspired by. Even more, he ignores those countries, or rather he only knows what their name suggests to his imagination, so flexible and rich that it may, by this kind of musical "radiesthesie", reach the essential reality of the theme more deeply than it would have by direct contact. This is where Tomasi appears to be the son of a land of a race, where the instinct, not yet halted by too artificial, too materialistic and too industrious a civilization still has the value of a guide and the infallibility of a natural law.

All in Tomasi's disposition reserves him for the theatre, and particularly the generous lyricism that seems to flow from his audacious pen. By a curious paradox, he however is the only of the four musicians that we are talking about today who has never written for the lyrical stage. We should precise that his name is often mentioned in the programmes of the Opéra or Opéra-Comique. Though he has met with remarkable success there with two ballets: La Grisi et La Rosière du village , he has not yet produced a lyrical drama as such.

On the contrary, nobody who is used to listening to radio ignores the admirable realizations that we owe him, in the field of broadcasted theatre. Tomasi has been one of the pioneers of this fresh art, which promises such beautiful results. Although the genre is not for the time being considered as linked to lyrical drama, I won't resist the desire to let you hear an extract of the work that you probably know, Tam-tam, both an attempt and a master-stroke of the broadcasted lyrical b theatre. Created in 1933, Tam-tam was born from Julien Maigret's collaboration and Heni Tomasi's. The work evokes a bush drama. Among the savage tribes of Ubangi, there is a white man, the manager of an advanced post. Completely incomprehensive of the deep poetry of the customs and traditions of the country, he laughs at them in front of his black common-law wife. He will die for this imprudence. The woman dulls his vigilance to the sounds of a bewitching monotonous song, the Chanson des Sables (Song of the Sands). This song is also a signal. The tom-tom, which from the beginning has been sputtering from a remote place, is approaching step by step. Its hammering, the natives' clamors, and the arabesques of Chanson des sables, everything are melting and dancing in an enchanting crescendo that will spark the final drama.

The following year, still in collaboration with Julien Maigret, Henri Tomasi released a new work for the radio, Ajax, a piece written in a beautiful dramatic way. He still works in this genre, in a regular collaboration with Georges Colin. Though his works are not as important as the first two, they nevertheless are interesting for this art of creating an atmosphere in which this musician has really become a master. 17 " This enthusiastic lecture is rather moving, if we try to imagine it with the doctoral tone and the solemnity of the time. It also suggests that Tomasi, through his regular contributions to the broadcasting productions, was already confirming his attraction to "music with a program" and passed for a well-identified celebrity by the radio listeners, even those who did not necessarily belong to the tiny part of the population concerned by classical music. This is confirmed in 1936 by the weekly TSF Programme. In an article entitled "Un compositeur aimé des sans-filistes : Henri Tomasi" (a composer loved by the radio listeners: Tomasi), the anonymous columnist says: "What seduces in his style: the impulsion of his melody, the richness of his instrumentation. Furthermore he dares, if necessary, to 'let his heart speak'. 18 " Though Tomasi's statements on radio and their echoes by the mediators of the specialized press and even some programs enlighten his convictions and his personality, they remain negligible compared to the numerous appearances of this musician on the broadcasting programs, either as a composer, or as a performer. The mentions of his name in the programs show the important space allowed to modern musicians on radio in the thirties.

II -A COMPOSER AND AN ORCHESTRA CONDUCTOR USUALLY MENTIONNED IN THE PROGRAMS

Radio-Paris enables the understanding of the distribution of the genres and types of programs in the musical supply of this station for the whole decade thirty 19 . Since this station, which was traditionally open to a "sophisticated broadcasting", used to provide with the highest precision the contents of most of its programs, this wide computation enables us to monitor, at a first time, how Tomasi's appearances occurred as an orchestra conductor.

AMONG RADIO-PARIS' ORCHESTRA CONDUCTORS

As soon as the musician joined Radio-Paris, he appears fifteen times as a conductor in our computation. In 1936, a year that stands out by an explosion of the musical slots on this station, one can count ten concerts broadcasted under his baton. The program is sometimes common to Radio-Colonial, since those network connections between public stations between public stations were rather usual. He is once at the helm of the Chamber orchestra of Concerts Poulet (on June 22 nd 1936), and several times at the musical conduction of a band probably issued from the station (the only title then is "Orchestre symphonique"). The Orchestre symphonique de Paris is usually broadcasted under his conduction (6 mentions of this orchestra over four distinct days). In 1938, he is still mentioned as the leader of the band, as well as three other times on a regular half-an-hour slot on Saturday evenings.

Based on a sampling of the ten months of the decade on Radio-Paris and Radio-LL / Radio-Cité, our computation includes 2,014 performers. Tomasi occupies the 42 nd rank (as classical performer / orchestra conductor) with a total of fifteen mentions, knowing that he is exclusively mentioned on Radio-Paris. Since the recurrence of the orchestra sequences or symphonic concerts is very strong from 1936 on, the appearances of conductor Tomasi on the waves occur at various moments of the day: in the end of the morning or the beginning of the afternoon slots (such as on Thursday June 22 nd 1936 from 11 am to 2 pm); at the beginning of the afternoon (on Wednesday June 10 th 1936 from 2.30 pm to 4 pm); in the end of the afternoon or beginning of the evening, with a half-an-hour interlude for the news (on Monday June 8 th 1936 from 6.30 to 7.30 pm); half an hour on Saturday evening on June 18 th 1938 from 10.05 to 10.35 pm), between a 40-minute slot of entertaining music (from 9.10 to 9.50 pm) and two hours of dancing music ("Jo Bouillon and his orchestra" from 11 pm to 1 am).

A constant fact on Radio-Paris during the whole decade, the slots where Tomasi leads an orchestra are sometimes split up by the performance of a female singer, who is either accompanied by the orchestra or a pianist. This is how the performers who are nowadays forgotten may have crossed the path of our conductor, for the whole length of a programme: 19 The whole musical programs of every month of June over the decade 1930 have been made in an inventory. Those represent 2,766 distinctive slots and 2,143 hours of programs. This computation generated 8,769 references of composers and 3,540 references of performers. The content of these broadcasting slots resemble those of the numerous "radio-concerts" and other "concerts symphoniques" which punctuate the programs of the stations of the thirties, and more particularly Radio-Paris', which was classically oriented. In this sampling of fifteen programmes one can find the inevitable ambassadors of the baroque period (Bach, Handel, Rameau, Purcell) and the classical one (Mozart, Haydn), pre-romantic (Beethoven, Schubert) and romantic (Brahms, Schumann, Chopin, Grieg, Lalo, Delibes). One can find another constant element of the thirties, which is the vast proportion of modern French musicians (d'Indy, Saint-Saëns), or even living musicians (Gaubert, Tailleferre, Bondeville, Levadé, Canteloube).

It was not possible to find recordings of programmes of th period with Tomasi leading an orchestra. The only archive that we were able to retrieve was produced in 1944. It is a recording of the final movement of Arthur Honegger's Rugby by Orchestre national. It shows that the broadcasting technique of the time hardly tolerated such a luxuriant sound and polytonal orchestral material20 .

Tomasi's broadcastings, as the orchestra conductor of the station, make him one of the ten most often broadcasted performers in our sampling of the programs of Radio-Paris for the period 1936-1939. On surveying this list of the most mentioned performers of the 1936-1939 period, one can't be astonished that Tomasi appears as a conductor, since he was hired by Radio-Paris from 1935 on, and was then usually broadcasted. The nine other performers are also used to the time schedule of the Paris station. They are broadcasted at least weekly, which explains the high number of those performers' mentions. This sampling shows that there is only one program in which Tomasi is mentioned both as a composer and a conductor. One can therefore not blame him for promoting his own works. One will indeed soon see that, without needing to promote his own music, Henri Tomasi largely benefited from the habits of the stations of the thirties and their broadcasting of modern French musicians. The only program when Tomasi is mentioned both as composer and conductor is scheduled on Monday June 1 st 1936. We can notice that the content of this program also confirms the already mentioned phenomenon: the usual presence of French composers, either living or at least belonging to the end of the 19 th / beginning of the 20 th century period. Apart from this piece by Tomasi there are indeed works by Lily Boulanger, Ernest Chausson, Camille Saint-Saëns and Vincent d'Indy. Radio-Paris, our template of the public stations, therefore favours the orchestras and their conductors. Through the principle of recurrent programs, the regular customers of the programs, including Henri Tomasi, are often mentioned in the program journals. The latter is also mentioned as a composer throughout the decade.

The ten most broadcasted performers on

Mentions of Tomasi both as a composer and a conductor

AN OFTEN BROADCASTED COMPOSER

Over the 2,185 composers of our computation, he sits at the 124 th rank with seventeen mentions (we also could add a 18 th considering the causerie musicale or musical talk of 1938 in which Louis Aubert mentions his work and proposes an excerpt from the work Tam-tam). By our reckoning , he appears in 1930, 1933, 1935, 1936, 1937, 1938 and 1939 21 .

On referring to the catalogue of his works published by the association of Henri Tomasi's friends 22 , one can see that by 1939 he had composed 62 works. In our sampling of the decade, out of the eighteen programs where he's mentioned as composer, one can count eight different works. Among those, one was broadcasted four times (O Ciuciarella 23 ), and another three times (Scènes municipales in their version for orchestra). The symphonic poem Tam-Tam, which we'll talk about later, is broadcasted twice. As for the other works, they appear only once in our computation. This is the case of Cynos, the 1929 symphonic poem, which was broadcasted under Eugène Bigot's baton on June 18 th 1930, performed by pianist Jean Doyen, a frequent performer in the broadcasted concert (at the 3 rd rank of our index of the performers, with no less than 44 appearances in the decade). We could also mention that the Cambodian dances were to be regularly scheduled for many years after their composition, for instance on Sunday December 29 th 1946 24 . By categorizing these works according to their title, one can see that the most suggestive themes in this sampling are exoticism and a description of the society, which brings us to the portrait that was made by Louis Aubert. By considering this table, we can put forward a hypothesis: most of the works that had already been composed by Tomasi were broadcasted. In fact, though Radio-Paris distinguishes itself by its high-flown broadcasting, it is obviously not the only station that broadcasted the works of modern composers, including Tomasi. Our sampling certainly shows only eight out of the sixty-two works that he had already composed in the interwar period. It however represents only one twelfth of it for this only station. It is very likely that a survey of the other stations and the other months than June would have hugely increased the list of Tomasi's broadcasted works, and confirmed the quotation presenting him as a "composer abundantly performed and recorded in his lifetime. As far as the circumstances of those broadcastings are concerned, one can notice that the orchestra conductors were able to illustrate the works of their counterparts works including: Eugène Bigot, Marius-François Gaillard, Raoul Labis, Roger Ellis, Maurice André, Albert Locatelli, or Godfroy Andolfi. Those works were scheduled in the "varied" programs as much as in the records mix, and Tomasi's works coexisted pell-mell, at times, with much older pieces, or works of vary different styles. One can survey the context of their appearance thanks to the content of the programs copied below:

The 11 mentioned works, classed by their number of broadcastings

The 18 programs in which Tomasi's pieces are mentioned Chants laotiens, Khène (Tomasi).

13:15 possibly different performers, the radio of the thirties reveals the links that some protagonists, including Tomasi, have been able to establish between the genres.

THE MUSICAL EXPRESSIONS OF THE TIME

By the diversity of his works and the repertoire that he was used to conducting, we could have set Henri Tomasi in the "cultural passers" categories of our indexes of authors and composers 29 . We only did so for the composers and performers whose connection with several musical genres (especially halfway between sophisticated and popular aesthetics) is visibly expressed in our sampling of the programmes. For example, Tomasi's melody inspired by Corsica, which was apparently very often broadcasted in classical concerts during the decade, was interpreted by Tino Rossi. As conductor, he conducted Aubert, Saint-Saëns, Gluck, Massenet, Wagner as much as Vincent Scotto (the friend with whom he wrote the music of the movie Colomba, which took José Luccioni to stardom status), or his own works.

As Frédéric Ducros implicitly explained, Tomasi's creation appetite brought him to stand alongside the artists of every horizon that he encountered, even though: "At 38, he escapes… taking his leave of everyone, his father, his wife, Ginette, 'a nice girl from Radio-Paris', the applause of the audience, that of Palais-Garnier, as well as of the ancient Orange theatre, he turns his back to the photographers, to the artists, whose works he had performed or those who created his own. Albert Wolf, Paul Paray, Eugène Bigot, society life, celebrities, Charles Dullin, Tino Rossi, César Vezzani, Joséphine Baker, Gabin, Brasseur, Morgan…… he puts an end to all this 'cinema'! On May 25 th 1939, he escapes from the screenplay that others had written […] 30 ." All these "other" artists evoked by the musicologist progress in professional sectors that are brought by narrowly connected mass industries: the movie industry, the record industry and the network of radio stations. Albeit it was felt as concurrent at the beginning, this medium eventually appears to be an ally, inseparable from the two others. This explosion of both supply and cultural demand sparks off a strange porosity of stylistic borders. Tomasi's music writing in the thirties is in keeping with this trend, as the diversity of artists he dealt with can prove.

As regards our broadcasting computation, his melodies inspired by Corsica are mainly the works that placed him at the crossroad of performers of very distant genres. We have seen that on Friday June 7 th 1935 his piece O Ciuciarella was mentioned right in the middle of a symphonic concert conducted by Marius-François Gaillard, with the collaboration of Miss Ninon Guérald from the Opéra-Comique. Some months later, we can actually read in the journal Radio-Magazine that chanteur de charme Tino Rossi "is used to singing earlier Corsican songs the masterpiece of which [precisely] is O Ciuciarella. 31 " Three years later, Le 29 Because their belonging to very diverse genres appeared in our samplings (which was not Tomasi's case), we created a group of 297 "passers", i.e. composers (including Vincent Scotto, Charles-Emile Waldteufel, Jean Wiener or Maurice Yvain) and 120 performers who can be styled "passers". 30 Henri Tomasi, un idéal méditerranéen, op. cit., p. 33. 31 Radio-Magazine #629 of November 3 rd 1935, p. 5: "Tino Rossi", by Jacques Maréchal. In the same article, the author indicates that the singer, after recording his version of "L'Aubade" of Lalo's Roi d'Ys, for Columbia, has, and at the very moment of his fabulous selling successes "just, beside the easy choruses, recorded two melodies by Reynaldo Hahn: Paysages and D'une Prison", commercial initiatives that make him an unexpected "passer performer".

Petit Radio tells in confidence that the Corsican female singer Lina Tosti "obviously has in her repertoire Corsican songs including this Ciuciarella by Henri Tomasi, whose melancholy she wonderfully expresses with tenderness and grace32 ". Female and male singers are the first that interpret the "passer composers". Even if around 1935 Tino Rossi fluctuates between his monotonous "latin lover" songs, Édouard Lalo's operatic arias, Reynaldo Hahn's operettas, and Henri Tomasi's folkloric Corsican songs, he remains above all a popular singer. Some lyrical artists however are "on the verge", so that it is not possible to qualify them either as prime done or female singer. For example, Miss Marie Simon "from the Paris Opera" sings melodies by Saint-Saëns33 but also performs in Paul Clérouc's entertaining programs34 . About her, Jacques Tem wrote the following: "Seduced from the beginning by Radio, by the infinite possibilities of this art, she has almost exclusively devoted herself to the broadcasting programs in which she brings a particularly varied repertoire. This repertoire actually stems from great lyrical works to light operetta, from classical melodies to entertainment.35 " It is therefore in a context of moving borders, perfectly embodied by broadcasting artists that Tomasi bridges the gap between works for the lyrical stage (he successfully created the ballet La Rosière du village in 1936 at the Paris Opera-Comique) and broadcasting productions that spontaneously crop up for this man deep-rooted in the land of his origins.

Among those productions, one expresses his attraction for faraway civilizations and also is the one in which all the musical resources inspired by his time come into play.

TAM-TAM AND THE POSTE COLONIAL

On June 13 th 1933, the French Radiodiffusion network proposed the very first federal broadcasting (that is to say simultaneously broadcasted on the whole or part of the state network) of the work Tam-tam, a "lyrical drama in two parts" by Jules Maigret. In Les Nouvelles Littéraires of July 8 th 1933, critic Pierre Descaves declared that he was convinced that this work, whose action is located at the core of Africa "is going to mark the annals of French broadcasting [with] its satanic cannibals, its stabbing dances, its heavy atmosphere, and its mysterious grandeur." According to the site of Henri Tomasi's friends, the composer, like Jules Verne, was a motionless traveler (should it be possible), a master in the art of those imaginary voyages so well described by critic and musicologist José Bruyr: "Twenty bars are enough for my disembarking in Brazil, Cambodia, Japan, for my landing on an African vermillion beach, or in a moon-lit clearing with tom-tom in the distance. 36 " Speaking of Tam-Tam, the piece we are interested in is mentioned among those which testify, in their inspirational roots, the "encounter of other beings, diverse and yet alike in their interrogation face to life and death, face to their human condition." Curiously, the "sketch lyrique en deux actes" Tam-tam is not listed on the catalogue among the seven pieces broadcasted, which are all qualified as: "designed to musically accompany radio productions that are not devoted to concert. 37 " The criteria might not have been sufficiently clear to consider this work as a musical one per se.

Anyway, this drama, the arrangement of a novel that Julien Maigret had published in 1927, was created on June 13 th 1933 on Radio-Paris and Le Poste Colonial in a technical transmission by the author. Composed by Henri Tomasi, the music is used in narrow association with the text. Many years later, the argument may appear a little melodramatic. It can be summed up as follows: a conceited black common-law wife, beaten up by her white partner, a brutal post manager at Ubangi, calls on her tribe for revenge. The convicted man hears the approaching tom-tom without understanding that it announces his imminent murder by cannibals. All the interest seems to stem from the increase of the dramatic tension and the strangeness of the atmosphere, served by the suggestive strength of the soundwaves. According to Pierre Descaves, this was a genuine "classic" of broadcasting drama Beyond a screenplay targeted to its audience and the then colonial empire, one can clearly see that this production highlights pieces that belong to a musical period which is culturally identifiable but expresses an aesthetic diversity.

As a conclusion of this paper about composer and conductor Henri Tomasi, through the prism of the musical broadcasting of the thirties, we will only summarize some of the observations resulting from our survey. First, the targeted press cuttings reveal a rather unknown part of the composer's life. They tell us both about Tomasi's conception of the medium (especially as a formidable means of acculturation of the masses) and the way in which much the latter appeared to be enjoyed by the listeners. What's more, this script of a broadcasting lecture that had disappeared (a genuine nugget) by Louis Aubert speaking about his colleague is astonishing in itself. The analysis is subtle and clearly matches the lasting image of Tomasi. It sounds as if Tomasi's style, on the verge of his forties, was already characteristic. Though he was going to produce works for some thirty more years, his portrait indeed matches Tomasi's work as a whole. Besides, his appearances on the waves, as composer as much as conductor, highlight the features of the radio of the thirties. There is a profusion of classical concerts or programs that mix the works of grand repertoire and lighter productions. Many French composers of the 20 th Century, including Tomasi, share the programs with sometimes unlikely neighbors. This dichotomy of the radio of the thirties between little songs and symphonic concerts can be found in the very sources of inspiration of our musician, enriched by the blossoming of the mass media in the interwar period. Incorporating every style, without rejecting any aesthetics, his symbiosis with the medium will probably have helped him to achieve a synthesis of the different qualities of those actors, composers or performers that we called "cultural passers". Tomasi perfectly fluctuates between two functions at the core of a medium that structurally absorbs all the styles. What was the weight of those experiences in the personal building of the musician, in his acquisition before his forties of the qualities specific to his work as a whole? Important, maybe, but let's leave the last word to an observer of the radio of the thirties who, speaking about this musician "so well-loved by the listeners", describes Tomasi's music as "so rich in its melody and its instrumentation, a music which knows how to speak to the heart."

Many thanks to Gérard Hocmard for his help with the language issues.

4

  For an outlook of the relations between musicians and the radio of the interwar period, one can read: Christophe Bennet, Musique et radio dans la France des années trente. La création d'un genre radiophonique, a PhD thesis in History of Music and Musicology, held on June 13 th 2007, under Michèle Alten's direcion, Paris-Sorbonne, 2 volumes, 942 p. This thesis was published under the following references: "La Musique à la Radio dans les années trente", Paris, L'Harmattan, 2010, 314 p. 5 Some newspapers remain visible at BnF and Inathèque de France: Choisir, TSF programme, Le Petit Radio, Mon programme et Radio-Magazine. 6 They can be consulted at Phonothèque de Radio France. 7 "Choisir" #210 of October 4 th 1936, p. 2: "Notes d'écoute".

21

  Musique et Radio dans la France des années trente, thesis cited. 22 Site: http://www.henri-tomasi.fr/ (consulted in July 2013). 23 The lullaby O Ciuciarella is extracted from Six mélodies populaires corses (#4). Composed in 1930, they had been created by Madeleine Whita and Orchestre des Concerts Lamoureux under Albert Wolff's conduction, on March 8 th 1931. 24 Concert of "varied music" on the station Programme parisien: conductor William Cantrelle with excerpts of Reynaldo Hahn's Bal de Béatrice d'Este (from 8.30 to 8.55).

  27 " 25 Le Marchand à la foire (U marcante in fiera) is the piece #2 from collection Les Cantu di Cirnu, written in 1933 and created on November 22 nd 1936 by Martha Angelici and the Orchestre Pasdeloup under the conduction of Henri Tomasi. 26 This is the suite for orchestra in four parts that was extracted by Henri Tomasi (from 1937) from his ballet . Let's recall here that this ballet in one act for choir and solo contralto (or mezzo soprano): screenplay by René Dumesnil. Created at the Opera de Paris on November 19 th 1938 under the baton of the composer. 27 Site of the "Association des amis d'Henri Tomasi", URL cited.

  : 1. Prélude, marine et chanson (Guy Ropartz), pour harpe, flûte, violon, violoncelle et alto, par le quintette Radio-Paris ; 2. L'amour d'une femme, extraits (Schumann) : a) Ai-je fait un rêve? b) Mon coeur, tu frémis, c) Ah! viens calmer ma fièvre, d) Tu peux lire dans mes yeux, Mlle Germaine Feraldy ; [à 21h30 : ] Suite de l'audition intégrale du Clavecin bien tempéré, de J.S. Bach, interprété par Albert Leveque. (Cinquième groupe) a) Prélude et fugue en si bémol majeur, n°21 ; b) [...] n°22 , c) [...] en si majeur n° 23, d) [...] en si mineur, n°24 ; 4. a) Deux mélodies corses (Tomasi) , d) Nell (Fauré) , c) Notre amour (Fauré), d) Sérénade (Strauss), Mlle Gerlaine Feraldy ; 5. Suite en parties (Vincent d'Indy), pour harpe, flûte, violon, violoncelle et alto, Le quintette Radio-Paris. [à 21h15 : revue de la presse du soir, informations et heure exacte de Longines] ancienne", Pièces en concert recueillies par Bazelaire (Couperin), violoncelle : Roger Boulmé : Allegro spirituoso et Sicilienne (Dalayrac) ; Célèbre gavotte, Passepied du jardinier (Lully) ; Ouverture de l'Epreuve villageoise (Grétry). -Musique française contemporaine. Pièces brèves (G. Ropartz) ; Le lied que chante mon amour, Menuet (Tomasi) ; Cloches dans la brume (Stalin) ; Quatre esquisses (Gaubert) ; Berceuse (Durosoir), violon : R. Krettly ; Zorriga (Bousquet) ; Pavane pur une infante défunte (Ravel) ; Divertissement sur des chansons ([?] lips) ; Miramar (Turina) ; Trois danses [...] (Rabaud) ; Arabesque (Montague Philmann) ; Suite pour cordes (Konguell). Orchestre dirigé par F. Gaillard, avec Mlle N. Guérald ; Le Calife de Bagdad, ouverture (Boieldieu) ; Petite Suite (Pierné) ; Les Zingaris cheminent (Gabriel-Marie) ; Paganini (F Lehar) ; Mélodies par Mlle N. Guérald : Adieu (Dussau) ; O Ciuciarella (Tomasi) ; Carmen (Clergue), solo de hautbois : M. Goubet, solo de violoncelle : M. Navarra ; Le Rouet d'Omphale, Poème symphonique (Saint-Saens) ; Pavane (G. Fauré) ; Peer Gynt (Grieg). de la TSF, orchestre [symphonique de Paris] dir. par Tomasi, avec Mme Arvez-Vernet : D'un soir triste ; d'un matin de printemps (Lily Boulanger) ; Prélude du deuxième acte de l'Etranger (d'Indy) ; Didon et Enée, Oh Zeus! ; Bellinde (Purcell) ; Au loin (Schumann) ; Le tilleul (Schubert) ; O Ciuciarella (Tomasi) ; L'attente (C. Saint-Saëns) ; Sérénade italienne (Chausson). Concert direction Labis. Orchestre de chambre de l'orchestre symphonique de Paris [suite] : Scènes municipales (Tomasi) ; Mélodies par M. Rudeau : Partir en voyage (Ordner) ; Je chante pour toi (Lehar) ; Tu m'as dit non (Rosen) ; Petit village (Nevi) ; Petite Suisse (Ducasse) ; Le Matin (Chaminade) ; La Verbena (Lacôme). Colonial) Concert symphonique, direction Roger Ellis : Euryanthe, ouverture (Weber) ; La Khovantchina : Entracte et danse des fées (Moussorgsky) ; Aux Etoiles (Duparc) ; Scènes napolitaines (Massenet). [à 12h15 :] Masques et bergamasques (Fauré) ; Les Maîtres chanteurs, extraits (Wagner) ; Danse castillane (J. Turina) ; Izeil, suite d'orchestre (G. Pierné) ; Cordoue en fête (Turina) ; Mélodies par Mlle Mildah Polia : Danza, Danza (Durante) ; A une jeune mariée (Nérini) ; Soir d'Idumée (Vellones) ; Ev'ry Tune, I fell the spirit (Harm. Burleigh) ; Tarentelle, flûte et clarinette solos (Saint-Saëns) ; Dom Quichotte, Entr'actes des 4e et 5e actes (Massenet) ; Marouf, danses (Rabaud) ; Scènes municipales (Tomasi). Colonial). Orchestre de chambre des concerts Poulet, direction M. Elie Schuyer : Ruy-Blas (Mendelssohn) ; Serenata (Braca) ; Fête de charité, suite d'orchestre (Lecocq) ; Danses hongroises (Brahms) ; Barcarolle (Tchaïkowsky) ; Espana (Waldteufel) ; Pavane (Fauré) ; Fêtes romaines (Fourdrain). [à 12h15 :] avec Madame Jeanne Eudes : Mireille, ouverture (Gounod) ; Extrême-Orient (de la Presle) ; Chant du soir (Schumann) ; Le Roi des Aulnes (Schubert) ; Scènes municipales (Tomasi) ; Phrynée (Saint-Saëns) ; Un Bouquet de Strauss (arr. A. Winter). Mélodies populaires de la famille Strauss ; Exiane (Doire) ; Engerrande (Chapuis) ; C'est le temple d'hiver ; Mon âme est en fleur (Lermyte) ; Suite Lorraine (Boisdeffre) ; La Bohème, fantaisie (Puccini). Mme Rosenfeld : C'est lui (Hugo Wolf) ; Sérénade à Ninon (Delibes) ; Le sourire, Sonnet champêtre (E. de Lassus) ; Chant de la mélancolie (Tomasi).

  M. L. Dufont : Les Saisons, air du Laboureur (Haydn) ; Le Voyageur (Fauré) ; La lune sur le bois se penche (Clergue) ; Chants laotiens, Khène (Tomasi).

  . The work was to be broadcasted twice during the following years (Radio-Paris on October 21 st 1936, and Radiodiffusion Nationale on January 5 th 1942). Announcing a new broadcasting on Radio-Paris on October 18 th 1936 we can read what follows: "M. Henri Tomasi's score is vastly adapted to the cruel mood of [the evocation of the imminent killing of a convicted man by the cannibals]. In this way it has already travelled all aver Europe. Backed by the strange rhythm of the tom-tom constantly amplified, there are worrying calls. The principal episodes of the piece are fortunately marked by a nostalgic tango: 'Disillusion', a foxtrot: 'Whisky', and a 'Song of the sands' full of very credible exoticism."

  Miss Meunier-Delince (on June 22 nd 1936); Miss Javogne (on June 29 th 1936); Mrs. Maria Branèze (on June 11 th 1938); Mrs. Deva-Dassy (on June 18 th 1938).

	date date	title title			content content		beginning end duration beginning end duration
			Orchestre de chambre symphonique Poste colonial. Concert
	date June 15 th 36 June 24 th 36	title Concert Symphonic Concert	content de Paris (O.S.P.) , dir. par Tomasi, symphonique, dir. Tomasi : Depuis le salon de la TSF, Orchestre symphonique de Paris dir. par Tomasi, avec Mme Arvez-Vernet : Niel : La création : Air de Gabriel Capricio italien (Tchaïkowsky) ; La avec Mlle Ina Niel : Suite de danses (Gabriel Pierné) ; 1812 (Tchaïkowsky) ; Mélodies par Mlle Symphonie en sol mineur, Concerto ; Les Heures dolentes (Dupont) ; pour clarinette et orchestre (Mozart)	beginning end duration 17:30 18:00 00:30 14:30 16:00 01:30
			D'un soir triste ; D'un matin de (Haydn) ; Berceuse (Mozart) ; Les Danse d'Abisag (Florent Schmitt).
	June 1 st 36	Concert	printemps (Lily Boulanger) ; Prélude noces de Jeannette ; Air du rossignol Orchestre symphonique de Paris du deuxième acte de l'Etranger (d'Indy) ; Didon et Enée, Oh Zeus! ; (Massé) . (O.S.P.) dir. par Tomasi, avec Mlle Suite du concert de l'Orchestre Javogne : Madrigal (Gaubert) ;	17:3	18 :00 00:30
	June 29 th 36	Concert	Bellinde (Purcell) ; Au loin (Schumann) ; Le tilleul (Schubert) ; symphonique de Paris, direction Tomasi : La vie pour le Tsar, Compliments (Schmitt) ; Sérénade (Hüe) ; A Napoli (Leleu). Pièces	17:30	18:00 00:30
			Venicarella (Tomasi) ; L'attente (C. ouverture (Glinka) ; Les saisons : pour violon : Intrada (Desplanes-
	June 15 th 36	Concert	Saint-Saëns) ; Sérénade italienne (Chausson). Chant du Faucheur, La moisson, Chant d'Autmone, En traineau, La Nachez) ; Guitare (Lalo) ; Le Cherrier (Wooleert).	18:30	19:25 00:55
			Suite du concert de l'Orchestre Fête de Noël (Tchaïkowsky) ; Concert symphonique, direction H.
			symphonique de Paris, direction L'album des six (Poulenc) ; Petite Tomasi, Mélodies par Mme Maria
	June 1 st 36 June 11 th 38	Concert Concert	: Prélude et cortège du quatrième Poste colonial. Concert françaises (Tailleferre) ; Trois Tomasi. Chaconne et rigaudon (Monsigny) ; Déjanire (Saint-Saëns) suite symphonique (Ch. Pons) ; Journée de mai (Haydn). Branèze : a) Etienne Marcel, air (Saint-Saëns) ; b) Six chansons	18:35 22:05	19:15 00:40 22:35 00:30
			acte ; Esquisses (Schumann) ; symphonique, dir. Tomasi : pastorales (Rivier).
	June 3 rd 36 June 17 th 36 June 18 th 38	Concert Symphonic Symphonic Concert Concert	Musiques pour films (Rhené-Baton). (Mendelssohn) ; Scherzo (Ed. Lalo) ; Saëns). pour violon et orchestre Parysatis, airs de ballet (Saint-Poste colonial. Concert symphonique, dir. M. H. Tomasi, avec M. Chedecal, violoniste : Symphonie (Schubert) ; Concerto Symphonie écossaise (Mendelssohn) Concert symphonique, direction H. ; Pièces françaises (Canteloube) ; Tomasi, Mélodies par Mme Deva-Danses espagnoles (Mozkowsky) ; Rédemption, fragment symphonique (Franck). Dassy : Mexico (Oberfeld) ; Yana (T. coeur de femme" ; b) "C'est toi" ; Richepin-Christiné) : a) "Si mon	14:30 14:30 22:05	16:00 01:30 16:00 01:30 22:35 00:30
			Divertissement pour violon et Mélodies, par M. René Hérent : a) Le
			orchestre (R. Bernard) ; Danses tambourin (J.-Ph. Rameau) ; b)
			norvégiennes (Grieg). Sérénade (Schubert)	;	c)
	June 25 th 38	Concert	Orchestre symphonique de Paris (O.S.P.) dir. par Tomasi : Les L'enterrement du Duc de Guise (Laparra) ; d) Le jardin d'amour	22:05	22:35 00:30
	June 8 th 36 June 22 nd 36	Concert Symphonic Concert	Hérétiques, ballet (Levadé) ; (Vuillermoz) ; Concert Mélodies par Mme Chalante : Cantate 57, Air de l'âme (Bach) ; Héraclès (Haendel) ; Air de symphonique, direction H. Tomasi : Les hérétiques, ballet (Levadé).	17:30 11:00	18:00 00:30 14:00 03:00
			l'Impatience (Rameau).
			Suite du concert de l'Orchestre
	June 8 th 36	Concert	symphonique de Paris, direction (Mozart) ; La Forêt enchantée Tomasi : Symphonie en ut majeur	18:35	19:30 00:55
			(d'Indy) ; Germania (Brahms).
			Poste	colonial.	Concert
	June 10 th 36	Symphonic Concert	symphonique,	dir.		14:30	16:00 01:30

Tomasi : Symphonie Pastorale (Beethoven) ; Valses (Schubert) ; Musiques intimes (F. Schmitt) ; Suite (A. Périlhou). (et Poste Colonial). Orchestre de chambre des Concerts Poulet, direction Henri Tomasi : Sinfonia brève (Inghelbrecht) ; Le Bal des Pendus (Bondeville) ; Fervaal (d'Indy) ; Concerto en fa (Gaubert) ; [à 12h15:] Valses de Schubert (orchestration Bigot) ; L'Enfant et les Sortilèges (Ravel) ; Suite carnavalesque (Erlanger) ; L'Ecole des Maris (Bondeville) ; Mélodies par Mlle Meunier-Delince : L'eau qui court (Alex. Georges[-Richepin]) ; Un Bal d'oiseaux (Lacôme) ; Silence amoureux (de Miollis [-Longas]) ; Ce n'était rien (R. Gérard) ; Mire dans mes yeux (Puget) ; Pas des fleurs (Delibes) ; La Bohème (Puccini) ; Préludes (Chopin). [à 12h45 : informations].

Radio-Paris of the 1936-1939 period

					References
	Rank	Performer	Category	Under-Category	on RP (1936-
					1939)
	1 Orchestre Victor Pascal	Classical band	Large band	27
	2	Orchestre Jo Bouillon (1936-1947)	Entertaining band	Entertaining orchestra	26
	3 Cloez, Gustave	Classical performer	Conductor	24
	4 Labis, Raoul	Classical performer	Conductor	18
	5 Doyen, Jean (1907-1982)	Classical performer Instrument player	18
	6 Orchestre national	Classical band	Large band	18
	7 Orchestre symph. de Paris	Classical band	Large band	17
	8 Bigot, Eugène (1888-1965)	Classical performer	Conductor	15
	9 Tomasi, Henri (1901-1971)	Classical performer	Conductor	15
	10 Orchestre Georges Bailly	Classical band	Large band	15

  Mathyl, Genio. Choeurs et orchestre sous la direction de M. Henry Defossé. 2. Cyrnos (H. Tomasi), poème symphonique pour piano et orchestre, M. Jean Doyen, soliste des concerts du Conservatoire, de Colonne, Lamoureux et Pasdeloup. Orchestre sous la direction de M. Eugène Bigot .

	date	title	contents	Tomasi's mention	Beginni ng
			Radio-Concert organisé par Radio-Magazine : 1. Louise
			(Gustave Charpentier), avec le concours de Mmes Marguerite
			Soyer, Abby Richardson, Andrée Vavon, Vacchino, Villette,
			Julliot, Holt, Gallet, Champagne, Mart, Carl ; MM. Micheletti,
	18-juin-	Radio-	Tubiana, Morturier,
	30	Concert

[à 20h30 revue sportive et à 21h15 : revue de la presse du soir. Informations et l'heure exacte Longines]

Cécile Méadel, Histoire de la radio des années trente, PhD in History, under Jean-Noël Jeanneney's direction, Institut d'Études Politiques of Paris, 1992. This thesis was published under the title: Histoire de la radio des années trente, Paris, Anthropos / INA, 1994.

René Duval, Histoire institutionnelle de la radio en France, PhD in "Sciences de l'information", Université de Paris II, 1979, published the same year: Histoire de la radio en France, Paris, Alain Moreau. The author clearly shows how the distribution of this audience at an early stage: households that where capable of buying a set, and technical fans who assembled the components themselves.

Cécile Méadel, "Programmes en masse, programmes de masse", in Régine Robin "Masse et culture de masse dans les années trente", Paris, Les éditions ouvrières, 1991 p. 56. By adding those who avoided to pay the broadcasting tax to the mass of supposed listeners, Cécile Méadel put forward the hypothesis that more than 56% of the inhabitants were within reach of a TSF set at the end of the thirties.

For a further comprehension of those debates, one can read chapter "Auditeurs, programmateurs et musiciens : des divergences de points de vue et d'intérêt" in La Musique à la Radio dans les années trente, op. cit., p. 83-111.

 12 Based on comments collected among the elite of the arts and literature, this study follows Georges Duhamel's polemical arguments on the issue. Over four editions of weekly Radio-Magazine (from November 20 th to December 11 th 1938), it overtakes the strict frame of the journal. In fact, the debate is widening until the columns of Le Figaro (including the conservative stances of Maurice Donnay and Maurice Dekobra) and those of the weekly Ici…Radio-Cité (where the manager of the station, Jean Antoine, expresses his reformist ambitions

).13 Radio-Magazine #789 of November 27 th 1938, p. 3: "Radio et Culture", by Pierre

Descaves. 14 The smooth flavor of a flat major is rapidly contradicted by the successive passages in f minor (bar 4) and b flat

minor (bar 5). 15 "Radio-Magazine" #749 of February 20 th 1938, p. 2-3: "Bureau des reclamations".

Histoire du théâtre lyrique en France, "de la Révolution à l'année 1900", tome 2, p. 265.

Histoire du théâtre lyrique en France, de la Révolution à l'année 1900, op. cit., p. 241. This lecture was broadcasted on Wednesday June 1 st 1938 on Radio-Paris [Source: Mon Programme].

TSF Programme #313 of September 11 th

1936: "Un compositeur aimé des sans-filistes : Henri Tomasi".

Phonothèque de l'INA, broadcasting of the first semester 1944 during Pierre de Coubertin's celebration in Lausanne: performance of the final of Honegger's Rugby by Orchestre national conducted by Henri Tomasi. Band referenced KO00084B ; X00235 à 38'41''

Le Petit Radio #547 of April 8 th 1938, p. 1: "Lina Tosti", by Jacques Tem.

In the recital she releases on Monday June 29 th 1936 on Radio-Paris (According to TSF-Programme).

Program "Les ondes de Paris" on June 22 nd 1938 (according to Le Petit Radio).

Le Petit Radio #570 of March 11 th 1938, p. 1: "Marie Simon, de l'Opéra", by Jacques Tem.

However, if Tomasi's works easily find room in so heterogeneous programs (according to present-day criteria), this is not only due to this improbable mixtures of that time. This is also because his work in itself reflects a deep orientation toward a multiform writing, without any genuine border between the styles and the genres.

III -AT A CROSSROAD OF MUTIPLES AESTHETICS

It is well known that Tomasi explored minor genres, especially by producing Métro Barbès, a tango-song of 1937 or Miomo, a "Corsican java" in 1938 28 . It is therefore natural that his work was interpreted by classical performers as well as by those specializing in more popular genres. An ultimate vector of communication between different aesthetics and