Abstract
The problem of speech recognition in the presence of interfering nonstationary noise is addressed. A method for noise reduction in the cepstral domain based on a multilayer network is proposed and tested on a large database of isolated words contaminated with nonstationary F-16 jet noise. The speech recognition system consists of an auditory preprocessing module, the cepstral noise reduction multilayer network, and a neural network classifier. The noise reduction network performs a nonlinear autoassociative mapping in the cepstral domain between a set of noisy cepstral coefficients and a set of noise-free cepstral coefficients. The average recognition rate on a test database was improved up to 65% when the noise reduction network was added to the speech recognition system.
| Original language | English |
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| Title of host publication | Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing |
| Volume | 2 |
| Publisher | IEEE Press |
| Publication date | 1991 |
| Pages | 933-936 |
| ISBN (Print) | 0780300041 |
| Publication status | Published - 1991 |
| Externally published | Yes |
| Event | 1991 IEEE International Conference on Acoustics, Speech and Signal Processing - Toronto, Canada Duration: 14 May 1991 → 17 May 1991 Conference number: 16 |
Conference
| Conference | 1991 IEEE International Conference on Acoustics, Speech and Signal Processing |
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| Number | 16 |
| Country/Territory | Canada |
| City | Toronto |
| Period | 14/05/1991 → 17/05/1991 |