The HEARSAY Speech Understanding System

Abstract

This talk describes the present state of performance of the HEARSAY system. [For more complete descriptions of the system see D. R. Reddy, L. D. Erman, and R. D. Neely, “A Model and a System for Machine Recognition of Speech,” IEEE Trans. Audio Electroacoust. AU-21, 229–238 (1973) and D. R. Reddy, L. D. Erman, R. D. Fennell, and R. B. Neely, “The HEARSAY Speech Understanding System : An Example of the Recognition Process,” Proc. 3rd Int. Joint Conf. on Artificial Intelligence (Aug. 1973)]. The system uses task and context-dependent information to help in the recognition of the utterance; this system consists of a set of cooperating parallel processes, each representing a different source of knowledge (e.g., acoustic-phonetic, syntactic, semantic). The knowledge is used either to predict what may appear in a given context or to verify an hypothesis resulting from a previous prediction. Performance data of the system on several tasks (e.g., medical diagnosis, news retrieval, chess, and programming) will be presented. For example: The voice-chess task contains a 31-word vocabulary with about 5 000 000 possible sentences. One particular set of data contains 19 utterances of three to nine (mean =4.5) words each. Seventy-nine percent of the utterances are correctly recognized (at about four times real time on a PDP10 computer); removing the semantic source of knowledge (but leaving the syntactic and acoustic-phonetic) reduces recognition to 42%.