G
Gael Richard
Researcher at Télécom ParisTech
Publications - 326
Citations - 7799
Gael Richard is an academic researcher from Télécom ParisTech. The author has contributed to research in topics: Source separation & Audio signal processing. The author has an hindex of 44, co-authored 316 publications receiving 7077 citations. Previous affiliations of Gael Richard include ParisTech & École Normale Supérieure.
Papers
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Proceedings ArticleDOI
Events Detection for an Audio-Based Surveillance System
TL;DR: The automatic shot detection system presented is based on a novelty detection approach which offers a solution to detect abnormality (abnormal audio events) in continuous audio recordings of public places and takes advantage of potential similarity between the acoustic signatures of the different types of weapons by building a hierarchical classification system.
Journal ArticleDOI
Signal Processing for Music Analysis
TL;DR: It is demonstrated that, to be successful, music audio signal processing techniques must be informed by a deep and thorough insight into the nature of music itself.
Journal ArticleDOI
Melody Extraction from Polyphonic Music Signals: Approaches, applications, and challenges
TL;DR: A case study that interprets the output of a melody extraction algorithm for specific excerpts and a comprehensive comparative analysis of melody extraction algorithms based on the results of an international evaluation campaign are provided.
Journal ArticleDOI
Source/Filter Model for Unsupervised Main Melody Extraction From Polyphonic Audio Signals
TL;DR: A new signal model is proposed where the leading vocal part is explicitly represented by a specific source/filter model and reaches state-of-the-art performances on all test sets.
Journal ArticleDOI
Fast approximated power iteration subspace tracking
TL;DR: This paper introduces a fast implementation of the power iteration method for subspace tracking, based on an approximation that is less restrictive than the well-known projection approximation, and guarantees the orthonormality of the subspace weighting matrix at each iteration.