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NOLISP
2005
Springer
13 years 10 months ago
Third-Order Moments of Filtered Speech Signals for Robust Speech Recognition
Novel speech features calculated from third-order statistics of subband-filtered speech signals are introduced and studied for robust speech recognition. These features have the p...
Kevin M. Indrebo, Richard J. Povinelli, Michael T....
NAACL
1994
13 years 6 months ago
Microphone-Independent Robust Signal Processing Using Probabilistic Optimum Filtering
A new mapping algorithm for speech recognition relates the features of simultaneous recordings of clean and noisy speech. The model is a piecewise nonfinear transformation appfied...
Leonardo Neumeyer, Mitch Weintraub
ICASSP
2010
IEEE
13 years 5 months ago
Optimizing spectral subtraction and wiener filtering for robust speech recognition in reverberant and noisy conditions
Speech enhancement is a common approach to address the effects of degradation due to noise and channel contamination. This approach is intended to suppress unwanted signal and rec...
Randy Gomez, Tatsuya Kawahara
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...