GENERALIZED MINIMAL DISTORTION SEGMENTATION FOR ANN-BASED SPEECH RECOGNITION
| dc.citation.epage | 145 | en_US |
| dc.citation.issue | 2 | en_US |
| dc.citation.spage | 141 | en_US |
| dc.citation.volume | 3 | en_US |
| dc.citation.woscount | 3 | |
| dc.contributor.author | CHEN, SH | en_US |
| dc.contributor.author | CHEN, WY | en_US |
| dc.contributor.department | 交大名義發表 | zh_TW |
| dc.contributor.department | 電信工程研究所 | zh_TW |
| dc.contributor.department | National Chiao Tung University | en_US |
| dc.contributor.department | Institute of Communications Engineering | en_US |
| dc.date.accessioned | 2014-12-08T15:03:30Z | |
| dc.date.available | 2014-12-08T15:03:30Z | |
| dc.date.issued | 1995-03-01 | en_US |
| dc.description.abstract | A generalized minimal distortion segmentation algorithm is proposed to solve the time alignment problem for ANN-based speech recognition. By modeling dynamics of spectral information of an acoustic segment with smooth curves obtained by orthonormal polynomial expansion, a speech signal is optimally divided into segments and then recognized by an MLP recognizer. Experimental results showed that the proposed method outperforms the standard CDHMM method. | en_US |
| dc.identifier.doi | 10.1109/89.366545 | en_US |
| dc.identifier.issn | 1063-6676 | en_US |
| dc.identifier.journal | IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING | en_US |
| dc.identifier.uri | http://dx.doi.org/10.1109/89.366545 | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/2021 | |
| dc.identifier.wosnumber | WOS:A1995QG92100004 | |
| dc.language.iso | en_US | en_US |
| dc.title | GENERALIZED MINIMAL DISTORTION SEGMENTATION FOR ANN-BASED SPEECH RECOGNITION | en_US |
| dc.type | Letter | en_US |