標題: GENERALIZED MINIMAL DISTORTION SEGMENTATION FOR ANN-BASED SPEECH RECOGNITION
作者: CHEN, SH
CHEN, WY
交大名義發表
電信工程研究所
National Chiao Tung University
Institute of Communications Engineering
公開日期: 1-三月-1995
摘要: 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.
URI: http://dx.doi.org/10.1109/89.366545
http://hdl.handle.net/11536/2021
ISSN: 1063-6676
DOI: 10.1109/89.366545
期刊: IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING
Volume: 3
Issue: 2
起始頁: 141
結束頁: 145
顯示於類別:期刊論文


文件中的檔案:

  1. A1995QG92100004.pdf