Prè-requis
Basics of signal processing..
Objectif du cours
The aim of this course is to span several domains of audio signal analysis including audio indexing (or machine listening), high-resolution audio spectral analysis, audio source separation, and audio transformations (3D sound rendering, sound effects and sound modifications).
Presentation : here
Organisation des séances
- 13,5 h theoretical lectures
- 10,5 h practical sessions (TP) in Matlab (or Python if preferred)
- Lectures are planned to be in French but slides will be in English
Mode de validation
Papers reading/analysis with written report and oral presentation.
Références
- Y. Grenier, R. Badeau, G. Richard « Polycopiés de cours sur le traitement du signal audio (in French) », Télécom ParisTech.
- M. Mueller, D. Ellis, A. Klapuri, G. Richard, Signal Processing for Music Analysis », IEEE Journ. on Selected Topics in Sig. Proc., October 2011..
Thèmes abordés
- Audio Indexing (machine Listening): audio signal analysis for content-based information retrieval (automatic music genre recognition, automatic musical instrument identification, tempo or downbeat estimation,…).
- Audio Transformations (3D rendering, sound effects, sound modifications): Physical and perceptual approaches (binaural/transaural techniques, head-related transfer functions, wave field synthesis,..). Digital sound effects (flanger, phaser, distortion, artificial reverberation,..). Timbral, scale and pitch modifications.
- Audio Source Separation: Audio demixing, linear and convolutive mixing models, underdetermined models, sparse models, DUET.
- High resolution audio spectral analysis: Sinusoidal models, beyond Fourier analysis, spectral MUSIC, ESPRIT
Les intervenants
Gaël Richard
(Télécom Paris)
Roland Badeau
(Télécom Paris)
