Title :

Real-time Audio Classification based on Mixture Models

Author(s) :

Baelde, Maxime [Auteur]
A-Volute [Roubaix]
MOdel for Data Analysis and Learning [MODAL]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Biernacki, Christophe [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Greff, Raphaël [Auteur]
A-Volute [Roubaix]

Conference title :

The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2017)

City :

La Nouvelle-Orléans

Country :

Etats-Unis d'Amérique

Start date of the conference :

2017-03-05

English keyword(s) :

Learning
Mixture model
Real-time
Audio identification
Statistical
Sound classification
Machine learning

HAL domain(s) :

Statistiques [stat]/Machine Learning [stat.ML]
Statistiques [stat]/Méthodologie [stat.ME]
Statistiques [stat]

English abstract : [en]

This is the poster related to the conference paper "A mixture model-based real-time audio sources classification method", Baelde et al, ICASSP 2017 (hal-01420677v2).This is the poster related to the conference paper "A mixture model-based real-time audio sources classification method", Baelde et al, ICASSP 2017 (hal-01420677v2).Show less >

Language :

Anglais

Peer reviewed article :

Non

Audience :

Internationale

Popular science :

Non

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL