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ICASSP
2011
IEEE
13 years 8 days ago
Non-negative matrix deconvolution in noise robust speech recognition
High noise robustness has been achieved in speech recognition by using sparse exemplar-based methods with spectrogram windows spanning up to 300 ms. A downside is that a large exe...
Antti Hurmalainen, Jort F. Gemmeke, Tuomas Virtane...
ICASSP
2010
IEEE
13 years 8 months ago
Optimizing spectral subtraction and wiener filtering for robust speech recognition in reverberant and noisy conditions
Speech enhancement is a common approach to address the effects of degradation due to noise and channel contamination. This approach is intended to suppress unwanted signal and rec...
Randy Gomez, Tatsuya Kawahara
INTERSPEECH
2010
13 years 3 months ago
Mask estimation in non-stationary noise environments for missing feature based robust speech recognition
In missing feature based automatic speech recognition (ASR), the role of the spectro-temporal mask in providing an accurate description of the relationship between target speech a...
Shirin Badiezadegan, Richard C. Rose
TASLP
2002
111views more  TASLP 2002»
13 years 8 months ago
Speech enhancement using a mixture-maximum model
We present a spectral domain, speech enhancement algorithm. The new algorithm is based on a mixture model for the short time spectrum of the clean speech signal, and on a maximum a...
David Burshtein, Sharon Gannot
ICMCS
2010
IEEE
164views Multimedia» more  ICMCS 2010»
13 years 8 months ago
Exploiting multimodal data fusion in robust speech recognition
This article introduces automatic speech recognition based on Electro-Magnetic Articulography (EMA). Movements of the tongue, lips, and jaw are tracked by an EMA device, which are...
Panikos Heracleous, Pierre Badin, Gérard Ba...