A Mandarin Voice Organizer Based on a Template-Matching Speech Recognizer

On the observation of current available voice organizers, all of them accept only voice commands or word-based commands. Using natural spoken language to operate organizer is still a difficult problem. In this paper, a template-based speech recognizer which accepts near(constrained) spoken language is proposed. Since the template-based recognizer is a domain-dependent speech recognition system, representing and matching of sentence templates become the main tasks of the recognizer. We use finate state networks(FSNs) to represent the sentence templates and propose a vowel-based, syllable-scoring method to match a correct template. By replacing the template sets, this method can be easily applied to other domains. Besides, two main functions, voice recording and voice message query, are implemented on our organizer using a fast CELP encoder/decoder to compress/decompress the voice data in realtime. Experimental results shows that the collected 31 sentence templates can greatly improve the voice interface between the user and the voice organizer.