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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Colla, A.M. |
| Copyright Year | 1989 |
| Description | Author affiliation: Elettronica San Giorgio, Genova, Italy (Colla, A.M.) |
| Abstract | A description is presented of AUTOSEGM, a novel method for automatic extraction of acoustic prototypes for large-vocabulary speech recognition systems based on diphone-like subword segments. AUTOSEGM compares favorably with previous methods for automatic extraction of diphone-like prototypes in that it does not require a set of training templates derived from another talker to bootstrap the new talker's prototypes. AUTOSEGM exploits only general speaker-independent acoustic/phonetic knowledge, in the form of a general language model and standard acoustic parameters (cepstral derivative, smoothed energy contour). The core of AUTOSEGM is a self-segmentation procedure: the speech material is segmented into pseudosyllables, within which some occurrences of the diphone-like segments are located. A recognition performance of about 78% correct for the top candidate was achieved in a large-vocabulary isolated word recognition task.< |
| Starting Page | 93 |
| Ending Page | 96 |
| File Size | 350355 |
| Page Count | 4 |
| File Format | |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.1989.266371 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1989-05-23 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Prototypes Vocabulary Speech recognition Loudspeakers Acoustic materials Automatic speech recognition Natural languages Decoding Acoustic signal detection Maintenance |
| Content Type | Text |
| Resource Type | Article |
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