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» Signal processing tools for speech recognition
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ICMI
2004
Springer
281views Biometrics» more  ICMI 2004»
14 years 1 months ago
Articulatory features for robust visual speech recognition
Visual information has been shown to improve the performance of speech recognition systems in noisy acoustic environments. However, most audio-visual speech recognizers rely on a ...
Kate Saenko, Trevor Darrell, James R. Glass
ICASSP
2010
IEEE
13 years 7 months ago
Finding emotionally involved speech using implicitly proximity-annotated laughter
Browsing through collections of audio recordings of conversation nominally relies on the processing of participants’ lexical productions. The evolving verbal and non-verbal cont...
Kornel Laskowski
ICASSP
2009
IEEE
14 years 2 months ago
A study on multilingual acoustic modeling for large vocabulary ASR
We study key issues related to multilingual acoustic modeling for automatic speech recognition (ASR) through a series of large-scale ASR experiments. Our study explores shared str...
Hui Lin, Li Deng, Dong Yu, Yifan Gong, Alex Acero,...
ICASSP
2008
IEEE
14 years 2 months ago
Unsupervised learning of auditory filter banks using non-negative matrix factorisation
Non-negative matrix factorisation (NMF) is an unsupervised learning technique that decomposes a non-negative data matrix into a product of two lower rank non-negative matrices. Th...
Alexander Bertrand, Kris Demuynck, Veronique Stout...
ICASSP
2010
IEEE
13 years 7 months ago
Information retrieval methods for automatic speech recognition
In this paper, we use information retrieval (IR) techniques to improve a speech recognition (ASR) system. The potential benefits include improved speed, accuracy, and scalability...
Xiaoqiang Xiao, Jasha Droppo, Alex Acero