Continuous speech recognition using large vocabulary word spotting and CV syllable spotting

A continuous-speech recognition system for Japanese text input is described. The system is speaker dependent and recognizes continuous phrasal speech. A consonant-vowel (CV) concatenation syllable lattice and a word lattice are generated from input speech using a vector-quantization-based continuous DP matching technique. These lattices are converted into Japanese written form using a word dictionary and grammatical information. Two methods for acoustic processing are proposed: a large vocabulary word spotting technique using high-frequency words and an optimization method for adjusting CV templates to a speaker by maximizing recognition accuracy. In recognition experiments, 500 words were selected as word templates, covering more than 90% of the technical words in reports written about X-ray computer tomography scanning. 1000 CV syllables were generated using these words. A word spotting accuracy of more than 70% and a CV spotting accuracy of 72% were obtained after iterative training. The CV spotting accuracy was improved by about 10% through iterative training