tailieunhanh - Báo cáo khoa học: "INTEGRATING MULTIPLE KNOWLEDGE SOURCES FOR DETECTION AND CORRECTION OF REPAIRS IN HUMAN-COMPUTER DIALOG*"

We have analyzed 607 sentences of spontaneous human-computer speech data containing repairs, drawn from a total corpus of 10,718 sentences. We present here criteria and techniques for automatically detecting the presence of a repair, its location, and making the appropriate correction. The criteria involve integration of knowledge from several sources: pattern matching, syntactic and semantic analysis, and acoustics. INTRODUCTION Spontaneous spoken language often includes speech that is not intended by the speaker to be part of the content of the utterance. . | INTEGRATING MULTIPLE KNOWLEDGE SOURCES FOR DETECTION AND CORRECTION OF REPAIRS IN HUMAN-COMPUTER DIALOG John Bear John Dowding Elizabeth Shribergj SRI International Menlo Park California 94025 ABSTRACT We have analyzed 607 sentences of spontaneous human-computer speech data containing repairs drawn from a total corpus of 10 718 sentences. We present here criteria and techniques for automatically detecting the presence of a repair its location and making the appropriate correction. The criteria involve integration of knowledge from several sources pattern matching syntactic and semantic analysis and acoustics. INTRODUCTION Spontaneous spoken language often includes speech that is not intended by the speaker to be part of the content of the utterance. This speech must be detected and deleted in order to correctly identify the intended meaning. The broad class of disfluencies encompasses a number of phenomena including word fragments interjections filled pauses restarts and repairs. We are analyzing the repairs in a large subset over ten thousand sentences of spontaneous speech data collected for the DARPA Spoken Language We have categorized these disfluencies as to type and frequency and are investigating methods for their automatic detection and correction. Here we report promising results on detection and correction of repairs by combining pattern matching syntactic and semantic analysis and acoustics. This paper extends work reported in an earlier paper This research was supported by the Defense Advanced Research Projects Agency under Contract ONR N00014-90-C-0085 with the Office of Naval Research. It was also supported by a Grant NSF IRI-8905249 from the National Science Foundation. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies either expressed or implied of the Defense Advanced Research Projects Agency of the . Government or of the .