Yann Bayle

Yann Bayle
University of Bordeaux · LaBRI, CNRS

Doctor of Engineering

About

17
Publications
4,544
Reads
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45
Citations
Citations since 2017
16 Research Items
45 Citations
2017201820192020202120222023024681012
2017201820192020202120222023024681012
2017201820192020202120222023024681012
2017201820192020202120222023024681012
Introduction
PhD in AI, Music Information Retrieval, Machine Learning, Signal Processing and Automatic Music Playlist Generation.
Additional affiliations
September 2015 - September 2018
French National Centre for Scientific Research
Position
  • PhD Student
Description
  • PhD Student in Music Information Retrieval, Signal Processing and Machine Learning
September 2015 - September 2018
Laboratoire Bordelais de Recherche en Informatique
Position
  • PhD Student
Description
  • PhD Student in Music Information Retrieval, Signal Processing and Machine Learning
September 2015 - September 2018
University of Bordeaux
Position
  • PhD Student
Description
  • PhD Student in Music Information Retrieval, Signal Processing and Machine Learning

Publications

Publications (17)
Article
Full-text available
Shark populations that are distributed alongside a latitudinal gradient often display body size differences at sexual maturity and vicariance patterns related to their number of tooth files. Previous works have demonstrated that Scyliorhinus canicula populations differ between the northeastern Atlantic Ocean and the Mediterranean Sea based on biolo...
Article
Full-text available
Vacuum tube amplifiers present sonic characteristics frequently coveted by musicians, that are often due to the distinct nonlinearities of their circuits, and accurately modelling such effects can be a challenging task. A recent rise in machine learning methods has lead to the ubiquity of neural networks in all fields of study including virtual ana...
Article
Full-text available
The present dataset contains the 3D models analyzed in Berio, F., Bayle, Y., Baum, D., Goudemand, N., and Debiais-Thibaud, M. 2022. Hide and seek shark teeth in Random Forests: Machine learning applied to Scyliorhinus canicula. It contains the head surfaces of 56 North Atlantic and Mediterranean small-spotted catsharks Scyliorhinus canicula, from w...
Article
Full-text available
Regionalization of the vertebral column occurred early during vertebrate evolution and has been extensively investigated in mammals. However, less data are available on vertebral regions of crown gnathostomes. This is particularly true for batoids (skates, sawfishes, guitarfishes, and rays) whose vertebral column has long been considered to be comp...
Article
Full-text available
This paper introduces SATIN, the Set of Audio Tags and Identifiers Normalized. SATIN is a database of 400k audio-related metadata and identifiers that aims at facilitating reproducibility and comparisons among the Music Information Retrieval (MIR) algorithms. The idea is to take advantage of partnerships between scientists and private companies tha...
Article
Full-text available
We introduce KaraMIR, a musical project dedicated to karaoke song analysis. Within KaraMIR, we define Kara1k, a dataset composed of 1000 cover songs provided by Recisio Karafun application, and the corresponding 1000 songs by the original artists. Kara1k is mainly dedicated toward cover song identification and singing voice analysis. For both tasks...
Thesis
Ce mémoire de thèse de doctorat présente, discute et propose des outils de fouille automatique de mégadonnées dans un contexte de classification supervisée musical.L'application principale concerne la classification automatique des thèmes musicaux afin de générer des listes de lecture thématiques.Le premier chapitre introduit les différents context...
Poster
Full-text available
Keywords: Signal processing, Machine learning, Data augmentation, Music Information Retrieval, Autotagging
Data
Poster from IEEE ISM 2017: Kara1k: a karaoke dataset for cover song identification and singing voice analysis. Explaining the new Kara1k dataset for cover song identification and singing voice analysis. Download below.
Conference Paper
Full-text available
We introduce Kara1k, a new musical dataset com- posed of 2,000 analyzed songs thanks to a partnership with a karaoke company. The dataset is divided into 1,000 cover songs provided by Recisio Karafun application http://www.karafun.com , and the corresponding 1,000 songs by the original artists. Kara1k is mainly dedicated toward cover song identific...
Article
Four experiments investigated change detection in acoustic scenes consisting of a sum of five amplitude-modulated pure tones. As the tones were about 0.7 octave apart and were amplitude-modulated with different frequencies (in the range 2–32 Hz), they were perceived as separate streams. Listeners had to detect a change in the frequency (experiments...
Article
This study deals with the classification of Instrumentals and Songs in a bigger musical database than what was used in all previous studies. Songs are musical pieces containing singing voice, contrary to Instrumentals. This research tackles the imbalance between the number of Instrumentals and the numerous Songs present in industrial musical databa...
Poster
Full-text available
Poster presented to describe the article published in CBMI 2017.
Conference Paper
Full-text available
This paper introduces SATIN, the Set of Audio Tags and Identifiers Normalized. SATIN is a database of 400k audio-related metadata and identifiers that aims at facilitating reproducibility and comparisons among the MIR algorithms. The idea is to take advantage of partnerships between scientists and private companies that host millions of tracks. Sci...
Poster
Full-text available
Presentation of current state-of-the-art, current progress and future work
Conference Paper
Full-text available
Le chant est un élément remarquable d’une chanson et sa détection automatique au sein d’un morceau est un défi largement étudié. Cet article propose une approche permettant de discriminer les titres musicaux comportant du chant dans une base de données musicales conséquente. L’approche précédemment proposée par Ghosal et al.[9] fonde la prise de dé...

Network

Cited By

Projects

Project (1)
Project
A perfect playlist needs 100% of precision even if a low recall is achieved. We apply this new paradigm in Song/Instrumental detection in big musical databases.