Comparison among time-delay neural networks, LVQ2 discrete parameter HMM and continuous parameter HMM
説明
A continuous-parameter hidden Markov model (HMM) is proposed and compared with a discrete-parameter HMM, a time delay neural network (TDNN), and LVQ2 by using the same training and testing database. It is found that the proposed model's performance is comparable to that of TDNN or LVQ2. Higher performance (96 approximately 97%) is obtained for all Japanese phonemes in isolated words. The HMM approach is superior to others for the recognition of time-sequential patterns like continuous speech. >
収録刊行物
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- International Conference on Acoustics, Speech, and Signal Processing
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International Conference on Acoustics, Speech, and Signal Processing 509-512, 2002-12-04
IEEE