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» Analysis-by-synthesis features for speech recognition
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INTERSPEECH
2010
13 years 4 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
ICMCS
2006
IEEE
140views Multimedia» more  ICMCS 2006»
14 years 3 months ago
Evolutionary Feature Generation in Speech Emotion Recognition
Feature sets are broadly discussed within speech emotion recognition by acoustic analysis. While popular filter and wrapper based search help to retrieve relevant ones, we feel th...
Björn Schuller, Stephan Reiter, Gerhard Rigol...
ICASSP
2011
IEEE
13 years 1 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
14 years 4 months ago
Irrelevant variability normalization based HMM training using map estimation of feature transforms for robust speech recognition
In the past several years, we’ve been studying feature transformation (FT) approaches to robust automatic speech recognition (ASR) which can compensate for possible “distortio...
Donglai Zhu, Qiang Huo
ICASSP
2008
IEEE
14 years 4 months ago
A study of using locality preserving projections for feature extraction in speech recognition
This paper presents a new approach to feature analysis in automatic speech recognition (ASR) based on locality preserving projections (LPP). LPP is a manifold based dimensionality...
Yun Tang, Richard Rose