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SPEECH
2010

Robust speech recognition by integrating speech separation and hypothesis testing

13 years 10 months ago
Robust speech recognition by integrating speech separation and hypothesis testing
Missing data methods attempt to improve robust speech recognition by distinguishing between reliable and unreliable data in the time-frequency domain. Such methods require a binary mask which labels time-frequency regions of a noisy speech signal as reliable if they contain more speech energy than noise energy and unreliable otherwise. Current methods for estimating the mask are based mainly on bottom-up speech separation cues such as harmonicity and produce labeling errors that cause a degradation in recognition performance. We propose a two stage recognition system in order to improve mask estimation and produce better recognition results. First, an n-best lattice consistent with the speech separation mask is generated. The lattice is then re-scored by expanding the mask using a model-based hypothesis test to determine the reliability of individual time-frequency regions. Systematic evaluations show significant improvement in recognition performance compared to that using speech se...
Soundararajan Srinivasan, DeLiang L. Wang
Added 30 Jan 2011
Updated 30 Jan 2011
Type Journal
Year 2010
Where SPEECH
Authors Soundararajan Srinivasan, DeLiang L. Wang
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