Structured Models for Joint Decoding of Repeated Utterances

G. Zweig, D. Bohus, X. Li, and P. Nguyen

Abstract

Due to speech recognition errors, repetition can be a frequent

occurrence in voice-search applications. While a proper treatment

of this phenomenon requires the joint modeling of two

or more utterances simultaneously, currently deployed systems

typically treat the utterances independently. In this paper, we

analyze the structure of repetitions and find that in at least one

commercial directory assistance application, repetitions follow

simple structural transformations more than 70% of the time.

We present preliminary results that suggest that significant gains

are possible by explicitly modeling this structure in a joint decoding

process.

Details

Publication typeInproceedings
Published inIn Proceedings of Interspeech
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