A Novel Independent Component Analysis for Noisy Speech Recognition
碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 95 === Independent component analysis (ICA) is a widely accepted mechanism in solving blind source separation (BSS) problem. In this study, we develop a new ICA approach for unsupervised learning and apply it for hidden Markov model (HMM) clustering and noisy speech...
Main Authors: | , |
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Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2007
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Online Access: | http://ndltd.ncl.edu.tw/handle/49923643104009055088 |