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.
|Number of pages||4|
|Journal||ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|
|State||Published - 1 Jan 1996|
|Event||Proceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6) - Atlanta, GA, USA|
Duration: 7 May 1996 → 10 May 1996