Rémi Foucard

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Expressing the similarity between musical streams is a challenging task as it involves the understanding of many factors which are most often blended into one information channel: the audio stream. Consequently, separating the musical audio stream into its main melody and its accompaniment may prove as being useful to root the similarity computation on a(More)
Short-term and long-term descriptors constitute complementary pieces of information in the analysis of audio signals. However, because they are extracted over different time horizons, it is difficult to exploit them concurrently in a fully effective manner. In this paper we propose a novel temporal fusion method that leverages the effectiveness of a given(More)
Automatic music classification aims at grouping unknown songs in predefined categories such as music genre or induced emotion. To obtain perceptually relevant results, it is needed to design appropriate features that carry important information for semantic inference. In this paper, we explore novel features and evaluate them in a task of music automatic(More)
Automatic tagging of music has mostly been treated as a classification problem. In this framework, the association of a tag to a song is characterized in a “hard” fashion: the tag is either relevant or not. Yet, the relevance of a tag to a song is not always evident. Indeed, during the ground-truth annotation process, several annotators may(More)
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