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» Signal processing tools for speech recognition
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ICMI
2004
Springer
281views Biometrics» more  ICMI 2004»
15 years 3 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
14 years 10 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
15 years 5 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
15 years 5 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
14 years 10 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