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AUDITORY MODEL BASED MODIFIED MFCC FEATURES
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0003-2638-6047
KTH, School of Electrical Engineering (EES), Sound and Image Processing.
2010 (English)In: 2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2010, 4590-4593 p.Conference paper, Published paper (Refereed)
Abstract [en]

Using spectral and spectro-temporal auditory models, we develop a computationally simple feature vector based on the design architecture of existing mel frequency cepstral coefficients (MFCCs). Along with the use of an optimized static function to compress a set of filter bank energies, we propose to use a memory-based adaptive compression function to incorporate the behavior of human auditory response across time and frequency. We show that a significant improvement in automatic speech recognition (ASR) performance is obtained for any environmental condition, clean as well as noisy.

Place, publisher, year, edition, pages
2010. 4590-4593 p.
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Keyword [en]
MFCC, auditory model, ASR
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-32258ISI: 000287096004126Scopus ID: 2-s2.0-78049372751ISBN: 978-1-4244-4296-6 (print)OAI: oai:DiVA.org:kth-32258DiVA: diva2:410990
Conference
2010 IEEE International Conference on Acoustics, Speech, and Signal Processing
Note
QC 20110415Available from: 2011-04-15 Created: 2011-04-11 Last updated: 2011-04-15Bibliographically approved

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Chatterjee, Saikat

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  • apa
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  • de-DE
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  • Other locale
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Output format
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