TAILIEUCHUNG - Báo cáo khoa học: "FACTORIZATION OF LANGUAGE CONSTRAINTS IN SPEECH RECOGNITION"

Integration of language constraints into a large vocabulary speech recognition system often leads to prohibitive complexity. We propose to factor the constraints into two components. The first is characterized by a covering grammar which is small and easily integrated into existing speech recognizers. The recognized string is then decoded by means of an efficient language post-processor in which the full set of constraints is imposed to correct possible errors introduced by the speech recognizer. . | FACTORIZATION OF LANGUAGE CONSTRAINTS IN SPEECH RECOGNITION Roberto Pieraccini and Chin-Hui Lee Speech Research Department AT T Bell Laboratories Murray Hill NJ 07974 USA ABSTRACT Integration of language constraints into a large vocabulary speech recognition system often leads to prohibitive complexity. We propose to factor the constraints into two components. The first is characterized by a covering grammar which is small and easily integrated into existing speech recognizers. The recognized string is then decoded by means of an efficient language post-processor in which the full set of constraints is imposed to correct possible errors introduced by the speech recognizer. 1. Introduction In the past speech recognition has mostly been applied to small domain tasks in which language consttaints can be characterized by regular grammars. All the knowledge sources required to perform speech recognition and understanding including acoustic phonetic lexical syntactic and semantic levels of knowledge are often encoded in an integrated manner using a finite state network FSN representation. Speech recognition is then performed by finding the most likely path through the FSN so that the acoustic distance between the input utterance and the recognized string decoded from the most likely path is minimized. Such a procedure is also known as maximum likelihood decoding and such systems are referred to as integrated systems. Integrated systems can generally achieve high accuracy mainly due to the fact that the decisions are delayed until enough information derived from the knowledge sources is available to the decoder. For example in an integrated system there is no explicit segmentation into phonetic units or words during the decoding process. All the segmentation hypotheses consistent with the introduced constraints are carried on until the final decision is made in order to maximize a global function. An example of an integrated system was HARPY Lowerre 1980 which integrated

Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.