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» Factor analysed hidden Markov models for speech recognition
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ICASSP
2010
IEEE
14 years 7 months ago
Model-based dereverberation in the logmelspec domain for robust distant-talking speech recognition
The REMOS (REverberation MOdeling for Speech recognition) concept for reverberation-robust distant-talking speech recognition, introduced in [1] for melspectral features, is exten...
Armin Sehr, Roland Maas, Walter Kellermann
TASLP
2002
96views more  TASLP 2002»
14 years 9 months ago
MAP speaker adaptation of state duration distributions for speech recognition
This paper presents a framework for maximum a posteriori (MAP) speaker adaptation of state duration distributions in hidden Markov models (HMM). Four key issues of MAP estimation, ...
Néstor Becerra Yoma, Jorge Silva Sán...
ISCAS
2007
IEEE
136views Hardware» more  ISCAS 2007»
15 years 4 months ago
Flexible Low Power Probability Density Estimation Unit For Speech Recognition
— This paper describes the hardware architecture for a flexible probability density estimation unit to be used in a Large Vocabulary Speech Recognition System, and targeted for m...
Ullas Pazhayaveetil, Dhruba Chandra, Paul Franzon
NIPS
2001
14 years 11 months ago
Dynamic Time-Alignment Kernel in Support Vector Machine
A new class of Support Vector Machine (SVM) that is applicable to sequential-pattern recognition such as speech recognition is developed by incorporating an idea of non-linear tim...
Hiroshi Shimodaira, K.-I. Noma, Mitsuru Nakai, Shi...
ICASSP
2009
IEEE
15 years 4 months ago
Speech emotion recognition via a max-margin framework incorporating a loss function based on the Watson and Tellegen's emotion m
This paper considers a method for speech emotion recognition by a max-margin framework incorporating a loss function based on a well-known model called the Watson and Tellegen’s...
Sungrack Yun, Chang D. Yoo