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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bonneau, H. Gauvain, J. |
| Copyright Year | 1987 |
| Description | Author affiliation: LIMSI/CNRS, Orsay, France (Bonneau, H.) |
| Abstract | In view of designing a speaker-independent large vocabulary recognition system, we evaluate a vector quantization approach to speaker adaptation. Only one speaker (the reference speaker) pronounces the application vocabulary. He also pronounces a small vocabulary called the adaptation vocabulary. Each new speaker then merely pronounces the adaptation vocabulary. Two adaptation methods are investigated, establishing a correspondence between the codebooks of these two speakers. This allows us to transform the reference utterances of the reference speaker into suitable references for the new speaker. Method I uses a transposed codebook to represent the new speaker during the recognition process whereas Method II uses a codebook which is obtained by clustering on the new speaker's pronunciation of the adaptation vocabulary. Experiments were carried out on a 20-speaker database (10 male, 10 female). The adaptation vocabulary contains 136 words; the application one has 104 words. The mean recognition error rate without adaptation is 22.3% for inter-speaker experiments; after one of the two methods has been implemented the mean recognition error rate is 10.5%. Comparison of performance of the two methods shows that a new speaker's codebook is not necessary to represent the new speaker. |
| Starting Page | 1434 |
| Ending Page | 1437 |
| File Size | 126310 |
| Page Count | 4 |
| File Format | |
| DOI | 10.1109/ICASSP.1987.1169537 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1987-04-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Vector quantization Vocabulary Books Speech recognition Testing Equations |
| Content Type | Text |
| Resource Type | Article |
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