Sciweavers

ICASSP
2011
IEEE

Frame-wise HMM adaptation using state-dependent reverberation estimates

12 years 7 months ago
Frame-wise HMM adaptation using state-dependent reverberation estimates
A novel frame-wise model adaptation approach for reverberationrobust distant-talking speech recognition is proposed. It adjusts the means of static cepstral features to capture the statistics of reverberant feature vector sequences obtained from distant-talking speech recordings. The means of the HMMs are adapted during decoding using a state-dependent estimate of the late reverberation determined by joint use of a feature-domain reverberation model and optimum partial state sequences. Since the parameters of the HMMs and the reverberation model can be estimated completely independently, the approach is very flexible with respect to changing acoustic environments. Due to the frame-wise model adaptation, some of the HMM limitations are relieved, and recognition results surpassing that of matched reverberant training are obtained at the cost of a moderately increased decoding complexity.
Armin Sehr, Roland Maas, Walter Kellermann
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Armin Sehr, Roland Maas, Walter Kellermann
Comments (0)