Integration of Acoustic and Linguistic Features for Maximum Entropy Speech Recognition
碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 93 === In traditional speech recognition system, we assume that acoustic and linguistic information sources are independent. Parameters of acoustic hidden Markov model (HMM) and linguistic n-gram model are estimated individually and then combined together to build a...
Main Authors: | , |
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Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2005
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Online Access: | http://ndltd.ncl.edu.tw/handle/24325293971312481529 |