Conference proceeding
Approximate Bayesian robust speech processing
2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), pp 397-400
Nov 2011
Abstract
We present a comparison of two variational Bayesian algorithms for joint speech enhancement and speaker identification. In both algorithms we make use of speaker dependent speech priors which allows us to perform speech enhancement and speaker identification jointly. For the first algorithm we work in the time domain and in the second we work in the log spectral domain. Our work is built on the intuition that speaker dependent priors would work better than priors that attempt to capture global speech properties. Experimental results using the TIMIT data set are presented to demonstrate the speech enhancement and speaker identification performance of the algorithms. We also measure perceptual quality improvement via the PESQ score.
Metrics
9 Record Views
Details
- Title
- Approximate Bayesian robust speech processing
- Creators
- Ciira Wa Maina - Drexel UniversityJohn MacLaren Walsh - Drexel University
- Publication Details
- 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), pp 397-400
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000410268000071
- Scopus ID
- 2-s2.0-84861313058
- Other Identifier
- 991019170479604721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Electrical & Electronic
- Telecommunications