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» Analysis-by-synthesis features for speech recognition
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ICASSP
2011
IEEE
13 years 1 months ago
Automatic speech recognition using Hidden Conditional Neural Fields
Hidden Conditional Random Fields(HCRF) is a very promising approach to model speech. However, because HCRF computes the score of a hypothesis by summing up linearly weighted featu...
Yasuhisa Fujii, Kazumasa Yamamoto, Seiichi Nakagaw...
ICASSP
2011
IEEE
13 years 1 months ago
Structured discriminative models for noise robust continuous speech recognition
Recently there has been interest in structured discriminative models for speech recognition. In these models sentence posteriors are directly modelled, given a set of features ext...
Anton Ragni, Mark John Francis Gales
IJON
2002
85views more  IJON 2002»
13 years 9 months ago
Learning statistically efficient features for speaker recognition
We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for a speaker. The basis functions learned by the algori...
Gil-Jin Jang, Te-Won Lee, Yung-Hwan Oh
TASLP
2008
148views more  TASLP 2008»
13 years 9 months ago
Combining Spectral Representations for Large-Vocabulary Continuous Speech Recognition
In this paper we investigate the combination of complementary acoustic feature streams in large vocabulary continuous speech recognition (LVCSR). We have explored the use of acoust...
Giulia Garau, Steve Renals
ICASSP
2010
IEEE
13 years 9 months ago
Investigations into prosodic syllable contour features for speaker recognition
We investigate various ways of generating prosodic syllable contour features that have recently been applied to enhance systems for speaker recognition. We compare different appro...
Marcel Kockmann, Lukas Burget, Jan Cernocký