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In the 2008 presidential election race in the United States, the prospective candidates made extensive use of YouTube to post video material. We developed a scalable system that transcribes this material and makes the content searchable (by indexing the meta-data and transcripts of the videos) and allows the user to navigate through the video material based on content. The system is available as an...
Interest continues in a class of robustness algorithms for speech recognition that exploit the notion of uncertainty introduced by environmental noise. These techniques share the property that the uncertainty varies with the noise level and is propagated to the decoding stage, resulting in increased model variances. In observation uncertainty forms, the uncertainty variance is simply the variance...
Standard noise compensation techniques for automatic speech recognition assume a clean trained acoustic model. What is thought of as "clean" data, may still have a variety of speakers, different channels and varying noise conditions. Hence it may be more reasonable to consider such data multi-conditional for multistyle training. This paper shows that multistyle models benefit from VTS compensation...
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