An event-synchronous signal processing system for connected-speech recognition

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 which 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 current approaches 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 an easy and a difficult vocabulary