An early-decision, real-time, connected-speech recognizer

It is often important that recognition decisions be made nearly instantaneously, i.e., early-decision, in applied connected-speech recognition systems. Therefore, many algorithms, which defer decisions until the end of an utterance, are unsuitable for these systems. This paper describes an early-decision recognizer, which has been operational at LEMS for about two years. For system-development purposes, the recognizer is programmed to reduce the data and make decisions sequentially using a multi-microprocessor implementation. While impractical for a development system, all algorithms are designed for a parallel, real-time, early-decision implementation. Connected-digit performance analysis, obtained from an automatic-evaluation system, is presented for ten male and ten female talkers. The reported evaluation has established a baseline word accuracy of 91.5%.