Several New DWT-based Methods for Noise-Robust Speech Recognition
碩士 === 國立暨南國際大學 === 電機工程學系 === 98 === The wavelet transform has been one of the most useful analysis tools in speech signal processing. Due to the better time-frequency localization and the multi-resolution characteristics, the wavelet is more suitable for analyzing non-stationary signals. In this t...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Online Access: | http://ndltd.ncl.edu.tw/handle/71276717981954818233 |