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ICASSP
2009
IEEE
13 years 11 months ago
Minimum variance modulation filter for robust speech recognition
This paper describes a way of designing modulation filter by datadriven analysis which improves the performance of automatic speech recognition systems that operate in real envir...
Yu-Hsiang Bosco Chiu, Richard M. Stern
ICASSP
2011
IEEE
12 years 8 months ago
Amplitude modulation spectrogram based features for robust speech recognition in noisy and reverberant environments
In this contribution we present a feature extraction method that relies on the modulation-spectral analysis of amplitude fluctuations within sub-bands of the acoustic spectrum by ...
Niko Moritz, Jörn Anemüller, Birger Koll...
ICASSP
2008
IEEE
13 years 11 months ago
Filter bank design based on minimization of individual aliasing terms for minimum mutual information subband adaptive beamformin
This paper presents new filter bank design methods for subband adaptive beamforming. In this work, we design analysis and synthesis prototypes for modulated filter banks so as t...
Ken'ichi Kumatani, John W. McDonough, S. Schachl, ...
INTERSPEECH
2010
12 years 11 months ago
Mask estimation in non-stationary noise environments for missing feature based robust speech recognition
In missing feature based automatic speech recognition (ASR), the role of the spectro-temporal mask in providing an accurate description of the relationship between target speech a...
Shirin Badiezadegan, Richard C. Rose
NIPS
2001
13 years 6 months ago
Sequential Noise Compensation by Sequential Monte Carlo Method
We present a sequential Monte Carlo method applied to additive noise compensation for robust speech recognition in time-varying noise. The method generates a set of samples accord...
K. Yao, S. Nakamura