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» Bi-Spectral Acoustic Features for Robust Speech Recognition
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NAACL
2003
13 years 8 months ago
Implicit Trajectory Modeling through Gaussian Transition Models for Speech Recognition
It is well known that frame independence assumption is a fundamental limitation of current HMM based speech recognition systems. By treating each speech frame independently, HMMs ...
Hua Yu, Tanja Schultz
CSL
2007
Springer
13 years 7 months ago
On noise masking for automatic missing data speech recognition: A survey and discussion
Automatic speech recognition (ASR) has reached very high levels of performance in controlled situations. However, the performance degrades significantly when environmental noise ...
Christophe Cerisara, Sébastien Demange, Jea...
CSL
2004
Springer
13 years 7 months ago
Factor analysed hidden Markov models for speech recognition
Recently various techniques to improve the correlation model of feature vector elements in speech recognition systems have been proposed. Such techniques include semi-tied covaria...
Antti-Veikko I. Rosti, M. J. F. Gales
ICASSP
2010
IEEE
13 years 7 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
LREC
2010
134views Education» more  LREC 2010»
13 years 9 months ago
Comparison of Spectral Properties of Read, Prepared and Casual Speech in French
In this paper, we investigate the acoustic properties of phonemes in three speaking styles: read speech, prepared speech and spontaneous speech. Our aim is to better understand wh...
Jean-Luc Rouas, Mayumi Beppu, Martine Adda-Decker