Spotting Japanese CV-syllables and phonemes using the time-delay neural networks

The authors present techniques for spotting Japanese CV syllables/phonemes in input speech based on TDNNs. They constructed a TDNN which can discriminate a single CV syllable or phoneme group. In Japanese, there are only about one hundred syllables, or fewer than 30 phonemes, which makes it feasible to prepare and train the TDNN to spot all possible syllables or phonemes extracted as training tokens from training words. Syllable and phoneme spotting experiments show excellent results, including a syllable spotting rate of better than 96.7% correct. These spotting techniques are proved to be a significant step toward continuous speech recognition.<<ETX>>