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ICASSP
2011
IEEE
14 years 3 months ago
Amplitude modulation spectrogram based features for robust speech recognition in noisy and reverberant environments
In this contribution we present a feature extraction method that relies on the modulation-spectral analysis of amplitude fluctuations within sub-bands of the acoustic spectrum by ...
Niko Moritz, Jörn Anemüller, Birger Koll...
ICASSP
2011
IEEE
14 years 3 months ago
Bayesian sensing hidden Markov models for speech recognition
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
George Saon, Jen-Tzung Chien
ICASSP
2011
IEEE
14 years 3 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
14 years 3 months ago
Speech enhancement using a joint map estimator with Gaussian mixture model for (non-)stationary noise
In many applications non-stationary Gaussian or stationary nonGaussian noises can be observed. In this paper we present a maximum a posteriori estimation jointly of spectral ampli...
Balázs Fodor, Tim Fingscheidt
ICASSP
2011
IEEE
14 years 3 months ago
Large vocabulary continuous speech recognition with context-dependent DBN-HMMS
The context-independent deep belief network (DBN) hidden Markov model (HMM) hybrid architecture has recently achieved promising results for phone recognition. In this work, we pro...
George E. Dahl, Dong Yu, Li Deng, Alex Acero