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» Independent component analysis for noisy speech recognition
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ICASSP
2011
IEEE
12 years 9 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...
IJON
2002
85views more  IJON 2002»
13 years 5 months ago
Learning statistically efficient features for speaker recognition
We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for a speaker. The basis functions learned by the algori...
Gil-Jin Jang, Te-Won Lee, Yung-Hwan Oh
NIPS
2004
13 years 6 months ago
Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis
In contrast to the equivalence of linear blind source separation and linear independent component analysis it is not possible to recover the original source signal from some unkno...
Tobias Blaschke, Laurenz Wiskott
INTERSPEECH
2010
13 years 8 days ago
Glottal-based analysis of the lombard effect
The Lombard effect refers to the speech changes due to the immersion of the speaker in a noisy environment. Among these changes, studies have already reported acoustic modificatio...
Thomas Drugman, Thierry Dutoit
ICASSP
2011
IEEE
12 years 9 months ago
Robust speaker identification using a CASA front-end
Speaker recognition remains a challenging task under noisy conditions. Inspired by auditory perception, computational auditory scene analysis (CASA) typically segregates speech by...
Xiaojia Zhao, Yang Shao, DeLiang Wang