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» The limits of speech recognition
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ICPR
2000
IEEE
14 years 10 months ago
A Markov Random Field Model for Automatic Speech Recognition
Speech can be represented as a time/frequency distribution of energy using a multi-band filter bank. A Markov random field model, which takes into account the possible time asynch...
Gérard Chollet, Guillaume Gravier, Marc Sig...
INTERSPEECH
2010
13 years 3 months ago
An improved wavelet-based dereverberation for robust automatic speech recognition
This paper presents an improved wavelet-based dereverberation method for automatic speech recognition (ASR). Dereverberation is based on filtering reverberant wavelet coefficients...
Randy Gomez, Tatsuya Kawahara
ICASSP
2011
IEEE
13 years 16 days ago
Non-stationary feature extraction for automatic speech recognition
In current speech recognition systems mainly Short-Time Fourier Transform based features like MFCC are applied. Dropping the short-time stationarity assumption of the voiced speec...
Zoltán Tüske, Pavel Golik, Ralf Schl&u...
ICASSP
2009
IEEE
14 years 3 months ago
Extended VTS for noise-robust speech recognition
Model compensation is a standard way of improving the robustness of speech recognition systems to noise. A number of popular schemes are based on vector Taylor series (vts) compen...
Rogier C. van Dalen, Mark J. F. Gales
TSD
2010
Springer
13 years 6 months ago
Hybrid HMM/BLSTM-RNN for Robust Speech Recognition
The question how to integrate information from different sources in speech decoding is still only partially solved (layered architecture versus integrated search). We investigate t...
Yang Sun, Louis ten Bosch, Lou Boves