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» The limits of speech recognition
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ICASSP
2008
IEEE
14 years 3 months ago
Irrelevant variability normalization based HMM training using map estimation of feature transforms for robust speech recognition
In the past several years, we’ve been studying feature transformation (FT) approaches to robust automatic speech recognition (ASR) which can compensate for possible “distortio...
Donglai Zhu, Qiang Huo
ICMCS
2005
IEEE
112views Multimedia» more  ICMCS 2005»
14 years 2 months ago
Segment-based approach to the recognition of emotions in speech
A new framework for the context and speaker independent recognition of emotions from voice, based on a richer and more natural representation of the speech signal, is proposed. Th...
Mohammad T. Shami, Mohamed S. Kamel
ICASSP
2011
IEEE
13 years 17 days ago
Large vocabulary continuous speech recognition with context-dependent DBN-HMMS
The context-independent deep belief network (DBN) hidden Markov model (HMM) hybrid architecture has recently achieved promising results for phone recognition. In this work, we pro...
George E. Dahl, Dong Yu, Li Deng, Alex Acero
ICASSP
2011
IEEE
13 years 16 days ago
Improved speaker recognition when using i-vectors from multiple speech sources
The concept of speaker recognition using i-vectors was recently introduced offering state-of-the-art performance. An i-vector is a compact representation of a speaker’s utteranc...
Mitchell McLaren, David A. van Leeuwen
ICASSP
2010
IEEE
13 years 9 months ago
Ultrasonic sensing for robust speech recognition
In this paper, we present our work using ultrasonic sensing of speech for digit recognition. First, a set of spectral ultrasonic features are developed and tuned in order to achie...
Sundararajan Srinivasan, Bhiksha Raj, Tony Ezzat