Event-Synchronous Signal Processing System for Connected-Speech Recognizer

摘要

Speech-source models indicate that event-synchronous feature analysis for a standard real-time speech recognizer (speaker-trained using dynamic programming) should provide a strong basis for improved performance. Among the problems that need to be addressed in implementing such a system are those of developing robust event (pitch, burst, etc.) detectors, synchronous-analysis methodologies, more meaningful feature sets, and algorithms for recognition, e.g., dynamic programming. Descriptions of the current approach to these problems for a left-to-right, connected-word recognizer are given. The event-synchronous system's performance, relative to standard asynchronous recognition methodologies, is presented for easy and difficult vocabularies.