44 citations · 142 across the 12 of their papers we have counts for
5 papers · 1 filter
Improving Collaborative Metric Learning with Efficient Negative Sampling
Viet-Anh Tran, Romain Hennequin, Jimena Royo-Letelier +1
Distance metric learning based on triplet loss has been applied with success in a wide range of applications such as face recognition, image retrieval, speaker change detection and…
Disambiguating Music Artists at Scale with Audio Metric Learning
Jimena Royo-Letelier, Romain Hennequin, Viet-Anh Tran +1
We address the problem of disambiguating large scale catalogs through the definition of an unknown artist clustering task. We explore the use of metric learning techniques to learn…
Music Mood Detection Based On Audio And Lyrics With Deep Neural Net
Rémi Delbouys, Romain Hennequin, Francesco Piccoli +2
We consider the task of multimodal music mood prediction based on the audio signal and the lyrics of a track. We reproduce the implementation of traditional feature engineering bas…
Audio Based Disambiguation Of Music Genre Tags
Romain Hennequin, Jimena Royo-Letelier, Manuel Moussallam
In this paper, we propose to infer music genre embeddings from audio datasets carrying semantic information about genres. We show that such embeddings can be used for disambiguatin…
Word2Vec applied to Recommendation: Hyperparameters Matter
Hugo Caselles-Dupré, Florian Lesaint, Jimena Royo-Letelier
Skip-gram with negative sampling, a popular variant of Word2vec originally designed and tuned to create word embeddings for Natural Language Processing, has been used to create ite…