Speech recognition in noisy conditions using missing feature approach (2001)
Abstract / truncated to 115 words
The research in this thesis addresses the problem of automatic speech recognition in noisy environments. Automatic speech recognition systems obtain acceptable performances in noise free conditions but these performances degrade dramatically in presence of additive noise. This is mainly due to the mismatch between the training and the noisy operating conditions. In the time-frequency representation of the noisy speech signal, some of the clean speech features are masked by noise. In this case the clean speech features cannot be correctly estimated from the noisy speech and therefore they are considered as missing or unreliable. In order to improve the performance of speech recognition systems in additive noise conditions, special attention should be paid to the ...
Information
- Author
- Renevey, Philippe
- Institution
- Swiss Federal Institute of Technology
- Supervisor
- Publication Year
- 2001
- Upload Date
- July 3, 2008
First few pages / click to enlarge
The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.
The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.