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Recognition and Correction of Voice Web Search Queries

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In this work we investigate how to recognize and correct voice web search queries. We describe our corpus of web search queries and show how it was used to improve recognition accuracy. We show that using a search-specific vocabulary with automatically generated pronunciations is superior to using a vocabulary limited to a fixed pronunciation dictionary. We conducted a formative user study to investigate recognition and correction aspects of voice search in a mobile context. In the user study, we found that despite a word error rate of 48%, users were able to speak and correct search queries in about 18 seconds. Users did this while walking around using a mobile touch-screen device.

For more details, there is a paper and video

Also see chapter 6 of my thesis

This will be a short talk with plently of time for questions. I will demo the system after the talk.

This talk is part of the Inference Group series.

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