This paper proposes three novel and effective procedures

for jointly analyzing repeated utterances. First, we propose

repetition-driven system switching, where repetition triggers

the use of an independent backup system for decoding. Second,

we propose a cache language model for use with the second

utterance. Finally, we propose a method with which the

acoustics from multiple utterances - not necessarily exact repetitions

of each other - can be combined to into a composite that

increases accuracy. The combination of all methods produces

a relative increase in sentence accuracy of 65.7% for repeated

voice-search queries.

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In  Interspeech 2009

Publisher  International Speech Communication Association
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