Conference proceeding
Joint Speech Enhancement and Speaker Identification Using Monte Carlo Methods
INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5, pp.1359-1362
01 Jan 2009
Abstract
We present an approach to speaker identification using noisy speech observations where the speech enhancement and speaker identification tasks are performed jointly. This is motivated by the belief that human beings perform these tasks jointly and that optimality may be sacrificed if sequential processing is used. We employ a Bayesian approach where the speech features arc modeled using a mixture of Gaussians prior. A Gibbs sampler is used to estimate the speech source and the identity of the speaker. Preliminary experimental results are presented comparing our approach to a maximum likelihood approach and demonstrating the ability of our method to both enhance speech and identify speakers.
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Details
- Title
- Joint Speech Enhancement and Speaker Identification Using Monte Carlo Methods
- Creators
- Ciira Wa Maina - Drexel Univ, Dept Elect & Comp Engn, Philadelphia, PA 19104 USAJohn MacLaren Walsh - Drexel Univ, Dept Elect & Comp Engn, Philadelphia, PA 19104 USAISCA-INST SPEECH COMMUN ASSOC
- Publication Details
- INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, VOLS 1-5, pp.1359-1362
- Conference
- INTERSPEECH 2009: 10TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2009, 10th
- Publisher
- Isca-Int Speech Communication Assoc
- Number of pages
- 4
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Identifiers
- 991019170408304721
InCites Highlights
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- Web of Science research areas
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic