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» Robust speech recognition using dynamic noise adaptation
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ICASSP
2011
IEEE
12 years 11 months ago
Non-linear noise compensation for robust speech recognition using Gauss-Newton method
In this paper, we present the Gauss-Newton method as a unified approach to optimizing non-linear noise compensation models, such as vector Taylor series (VTS), data-driven parall...
Yong Zhao, Biing-Hwang Juang
ICASSP
2011
IEEE
12 years 11 months ago
Delta-spectral cepstral coefficients for robust speech recognition
Almost all current automatic speech recognition (ASR) systems conventionally append delta and double-delta cepstral features to static cepstral features. In this work we describe ...
Kshitiz Kumar, Chanwoo Kim, Richard M. Stern
INFORMATICALT
2010
107views more  INFORMATICALT 2010»
13 years 6 months ago
Optimization of Formant Feature Based Speech Recognition
The paper deals with the use of formant features in dynamic time warping based speech recognition. These features can be simply visualized and give a new insight into understanding...
Antanas Lipeika
ICASSP
2011
IEEE
12 years 11 months ago
Factor analysis based VTS and JUD noise estimation and compensation
Model based compensation schemes are a powerful approach for noise robust speech recognition. Recently there have been a number of investigations into adaptive training, and estim...
Federico Flego, Mark John Francis Gales
TASLP
2010
157views more  TASLP 2010»
13 years 2 months ago
HMM-Based Reconstruction of Unreliable Spectrographic Data for Noise Robust Speech Recognition
This paper presents a framework for efficient HMM-based estimation of unreliable spectrographic speech data. It discusses the role of Hidden Markov Models (HMMs) during minimum mea...
Bengt J. Borgstrom, Abeer Alwan