Recognition of phonemes in continuous speech using a modified LVQ2 method

概要

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This paper proposed a new phoneme recognition method based on the Learning Vector Quatization(LVQ2)algorithm proposed by Kohonen. We propose three versions of a modified training algorithm to overcome a shortcoming of the LVQ2 method. In the modified LVQ2 algorithm, p reference vectors are modified at the same time if the correct class in within the N-th rank where N is set to some constant. Using this algorithm, the phoneme recognition scores obtained by the modified LVQ2 algorithm were higher than those obtained by the original LVQ2 algorithm. Furthermore, we propose a segmentation and recognition method for phonemes in continuous speech. At first a likelihood matrix is computed using the reference vectors, where each row indicates the likelihood sequence of each phoneme and each column indicates the likelihood of all phonemes for each 10-ms unit. The optimum phoneme sequence is computed from the likelihood matrix using the DP with duration constraints. We applied this method to a multi-speaker-dependent phoneme recognition task for continuous speech uttered Bunsetsu by Bunsetsu. The phoneme recognition score was 85. 5% for the speech samples in continuous speech.
社団法人日本音響学会の論文