Continuous Mandarin speech recognition using hierarchical recurrent neural networks

Yuan Fu Liao*, Wen Yuan Chen, Sin-Horng Chen

*此作品的通信作者

研究成果: Conference article同行評審

3 引文 斯高帕斯(Scopus)

摘要

An ANN-based continuous Mandarin base-syllable recognition system is proposed. It adopts a hybrid approach to combine an HRNN with a Viterbi search. The HRNN is taken as a frond-end processor and responsible for calculating discrimination scores for all 411 base-syllables. The Viterbi search is then followed to find out the best base-syllable sequence with highest score as the recognized output. Experimental results showed that the proposed system outperforms the conventional HMM method on both the recognition accuracy and the computational complexity. The system can also be further modified to reduce the computational complexity while retaining the recognition accuracy almost be undegraded.

原文English
文章編號550600
頁(從 - 到)3370-3373
頁數4
期刊ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
6
DOIs
出版狀態Published - 9 五月 1996
事件Proceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6) - Atlanta, GA, USA
持續時間: 7 五月 199610 五月 1996

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