A novel approach using modulation features for multiphone-based speech recognition

Recent advances in coherent and convex demodulation have proven useful for analyzing and modifying the low-frequency envelope structure of speech. This paper reports the application of both methods, referred to here as bandwidth-constrained demodulation, to large-scale speech recognition in the form...

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Bibliographic Details
Published in2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 5264 - 5267
Main Authors Clark, Pascal, Sell, Gregory, Atlas, Les
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2011
Subjects
Convex optimization
Demodulation
Feature extraction
Frequency modulation
Hidden Markov models
Modulation
Speech
Speech processing
Speech recognition
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Summary:Recent advances in coherent and convex demodulation have proven useful for analyzing and modifying the low-frequency envelope structure of speech. This paper reports the application of both methods, referred to here as bandwidth-constrained demodulation, to large-scale speech recognition in the form of new feature representations. Modulation-based features yielded measurable improvement when included as complementary sources of information with a baseline recognizer. Furthermore, both sets of demodulation features showed promise for outperforming the conventional Hilbert envelope method which underlies most modern speech recognition features. These experimental results show the potential for further development in feature representations based on recently-developed bandwidth-constrained modulation signal models.
ISBN:9781457705380
1457705389
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2011.5947545