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ICMCS
2005
IEEE
133views Multimedia» more  ICMCS 2005»
13 years 11 months ago
Multi-sensory speech processing: incorporating automatically extracted hidden dynamic information
We describe a novel technique for multi-sensory speech processing for enhancing noisy speech and for improved noiserobust speech recognition. Both air- and bone-conductive microph...
Amarnag Subramanya, Li Deng, Zicheng Liu, Zhengyou...
TSD
2007
Springer
13 years 12 months ago
TRAP-Based Techniques for Recognition of Noisy Speech
Frantisek Grézl, Jan Cernocký
ICASSP
2011
IEEE
12 years 9 months ago
Machine and acoustical condition dependency analyses for fast acoustic likelihood calculation techniques
The acceleration of acoustic likelihood calculation has been an important research issue for developing practical speech recognition systems. And there are various specification ...
Atsunori Ogawa, Satoshi Takahashi, Atsushi Nakamur...
TASLP
2011
13 years 21 days ago
Advances in Missing Feature Techniques for Robust Large-Vocabulary Continuous Speech Recognition
— Missing feature theory (MFT) has demonstrated great potential for improving the noise robustness in speech recognition. MFT was mostly applied in the log-spectral domain since ...
Maarten Van Segbroeck, Hugo Van Hamme
INTERSPEECH
2010
13 years 17 days ago
Artificial and online acquired noise dictionaries for noise robust ASR
Recent research has shown that speech can be sparsely represented using a dictionary of speech segments spanning multiple frames, exemplars, and that such a sparse representation ...
Jort F. Gemmeke, Tuomas Virtanen