A Speech-First Model for Repair Detection and Correction
نویسندگان
چکیده
Interpreting fttUy natural speech is an important goal for spoken language understanding systems. However, while corpus studies have shown that about 10% of spontaneous utterances contain selfcorrections, or REPAIRS, little is known about the extent to which cues in the speech signal may facilitate repair processing. We identify several cues based on acoustic and prosodic analysis of repairs in the DARPA Air Travel In.formation System database, and propose methods for exploiting these cues to detect and correct repairs.
منابع مشابه
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