Large vocabulary speaker-independent Japanese speech recognition system

This paper describes the speaker independent large vocabulary speech recognition system based on phoneme recognition. Phoneme recognition employs LPC cepstrum coefficients as the feature parameter and statistical distance measure between an input pattern and phoneme reference template. Using power dips of low and high frequency range, similarity to unvoiced feature and similarity to nasal feature, the consonant segments are detected. The discrimination of phonemes is performed individually for vowels, semi-vowels and consonants. Phoneme sequence which is result of phoneme recognition is matched with each item of the word dictionary and the item with the highest similarity in the dictionary is output as the recognition result. An average phoneme recognition score is 81.4% for 212 words uttered by forty speakers including males and females; 90.6% for vowels, 78.0% for semivowels and 71.9% for consonants. An average score of word recognition is 95.6% for 274 Japanese city names uttered by forty speakers.