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Continuous Mandarin speech recognition using hierarchical recurrent neural networks

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3 Author(s)
Yuan-Fu Liao ; Nat. Chiao Tung Univ., Hsinchu, Taiwan ; Wen-Yuan Chen ; Sin-Horng Chen

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 at a front-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 ungraded

Published in:

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on  (Volume:6 )

Date of Conference:

7-10 May 1996

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