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ICASSP
2008
IEEE
13 years 11 months ago
Adaptation of compressed HMM parameters for resource-constrained speech recognition
Recently, we successfully developed and reported a new unsupervised online adaptation technique, which jointly compensates for additive and convolutive distortions with vector Tay...
Jinyu Li, Li Deng, Dong Yu, Jian Wu, Yifan Gong, A...
INTERSPEECH
2010
12 years 12 months ago
HMM adaptation using linear spline interpolation with integrated spline parameter training for robust speech recognition
We recently proposed a method for HMM adaptation to noisy environments called Linear Spline Interpolation (LSI). LSI uses linear spline regression to model the relationship betwee...
Michael L. Seltzer, Alex Acero
ICASSP
2008
IEEE
13 years 11 months ago
HMM adaptation using a phase-sensitive acoustic distortion model for environment-robust speech recognition
In this paper, we present a new approach to HMM adaptation that jointly compensates for additive and convolutive acoustic distortion in environment-robust speech recognition. The ...
Jinyu Li, Li Deng, Dong Yu, Yifan Gong, Alex Acero
ICASSP
2011
IEEE
12 years 8 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 th...
Armin Sehr, Roland Maas, Walter Kellermann
NIPS
1998
13 years 6 months ago
Controlling the Complexity of HMM Systems by Regularization
This paper introduces a method for regularization of HMM systems that avoids parameter overfitting caused by insufficient training data. Regularization is done by augmenting the E...
Christoph Neukirchen, Gerhard Rigoll