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» The limits of speech recognition
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INTERSPEECH
2010
13 years 3 months ago
Canonical state models for automatic speech recognition
Current speech recognition systems are often based on HMMs with state-clustered Gaussian Mixture Models (GMMs) to represent the context dependent output distributions. Though high...
Mark J. F. Gales, Kai Yu
ICASSP
2011
IEEE
13 years 17 days 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
13 years 17 days ago
Rapid joint speaker and noise compensation for robust speech recognition
For speech recognition, mismatches between training and testing for speaker and noise are normally handled separately. The work presented in this paper aims at jointly applying sp...
K. K. Chin, Haitian Xu, Mark J. F. Gales, Catherin...
ICASSP
2011
IEEE
13 years 17 days ago
Non-stationary noise estimation method based on bias-residual component decomposition for robust speech recognition
This paper addresses a noise suppression problem, namely the estimation of non-stationary noise sequences. In this problem, we assume that non-stationary noise can be decomposed i...
Masakiyo Fujimoto, Shinji Watanabe, Tomohiro Nakat...
ICASSP
2009
IEEE
14 years 3 months ago
Independent component analysis for noisy speech recognition
Independent component analysis (ICA) is not only popular for blind source separation but also for unsupervised learning when the observations can be decomposed into some independe...
Hsin-Lung Hsieh, Jen-Tzung Chien, Koichi Shinoda, ...