頁籤選單縮合
題 名 | A New SCHMM/MNN Hybrid Model for Mandarin Speech Recognition |
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作 者 | 仝興倫; 莊堯棠; | 書刊名 | Journal of Information Science and Engineering |
卷 期 | 13:2 1997.06[民86.06] |
頁 次 | 頁355-365 |
專 輯 | Special Issue on Neural Networks |
分類號 | 312.23 |
關鍵詞 | Mandarin speech recognition; Semi-continuous hidden markov model; Parallel distribution processing; Fine classification; |
語 文 | 英文(English) |
英文摘要 | In this paper, we propose a new scheme that combines the semi- continuous hidden Markov model (SCHMM) and modular neural networks (MNN) to recognize isolated Mandarin syllables. The SCHMM formulation has been proven successful in modeling the temporal arrangement of speech signals, and MNN is also suitable for performing static pattern classification. In the scheme described here, SCHMM outputs establish the sequence of observation vectors to be inputs of the MNN. Experimental results show that by combining both the discriminative power of MNN and the capability of modeling the temporal variations of an SCHMM into a hybrid model, speech recognition performance is significantly improved. |
本系統中英文摘要資訊取自各篇刊載內容。