Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste

Recommender systems are increasingly used to predict and serve content that aligns with user taste, yet the task of matching new users with relevant content remains a challenge. We consider podcasting to be an emerging medium with rapid growth in adoption, and discuss challenges that arise when applying traditional recommendation approaches to address the cold-start problem. Using music consumption behavior, we examine two main techniques in inferring Spotify users preferences over more than 200k podcasts. Our results show significant improvements in consumption of up to 50\% for both offline and online experiments. We provide extensive analysis on model performance and examine the degree to which music data as an input source introduces bias in recommendations.Comment: SIGIR 202

Algorithmes évolutionnistes appliqués à l'extraction de caractéristiques pour la reconnaissance du locuteur

L'étape d'extraction de caractéristiques occupe une place fondamentale dans les systèmes de reconnaissance des formes. Ces travaux de thèse portent sur l optimisation de ce module de traitement pour la tâche de reconnaissance du locuteur par Algorithmes Evolutionnistes (AEs). Nous avons évalué cette approche pour la tâche de segmentation et le regroupement du locuteur (SRL) ainsi que pour la tâche de vérification automatique du locuteur, dans le cadre des campagnes d'évaluation ESTER 2005 et Nist 2006.Les différentes études réalisées montrent que l'utilisation d'AE pour l'optimisation du module de codage permet d'améliorer les performances des systèmes. De plus ces travaux montrent qu'une amélioration significative des résultats est possible par l'utilisation de deux codeurs complémentaires. Nous avons, dans ce contexte, développé un algorithme évolutionniste permettant d'optimiser la complémentarité des extracteurs de caractéristiques.PARIS-BIUSJ-Mathématiques rech (751052111) / SudocSudocFranceF

GMM supervector for Content Based Music Similarity

cote interne IRCAM: Charbuillet11aNone / NoneNational audienceGMM supervector for Content Based Music Similarit

Production Effect: Audio Features For Recording Techniques Description And Decade Prediction

cote interne IRCAM: Tardieu11aNone / NoneNational audienceIn this paper we address the problem of the description of music production techniques from the audio signal. Over the past decades sound engineering techniques have changed drastically. New recording technologies, extensive use of compressors and limiters or new stereo techniques have deeply modified the sound of records. We propose three features to describe these evolutions in music production. They are based on the dynamic range of the signal, energy difference between channels and phase spread between channels. We measure the relevance of these features on a task of automatic classification of Pop/Rock songs into decades. In the context of Music Information Retrieval this kind of description could be very useful to better describe the content of a song or to assess the similarity between songs

A fast algorithm for music search by similarity in large databases based on modified Symetrized Kullback Leibler Divergence

cote interne IRCAM: Charbuillet10aInternational audienceA fast algorithm for music search by similarity in large databases based on modified Symetrized Kullback Leibler Divergenc

Multi Filter Bank Approach for Speaker Verification Based on Genetic Algorithm

International audienc

Qualitative Comparison of Audio and Visual Descriptors Distributions

Abstract—A comparative study of distributions and properties of datasets representing public domain audio and visual content is presented. The criteria adopted in this study incorporate the analysis of the pairwise distance distribution histograms and estimation of intrinsic dimensionality. In order to better understand the results, auxiliary datasets have been also considered and analyzed. The results of this study provide a solid ground for further research using the presented datasets such as their indexability with index structures. I