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Speech enhancement via combination of Wiener filter and blind source separation
KTH, School of Electrical Engineering (EES), Communication Theory.
KTH, School of Electrical Engineering (EES), Communication Theory.
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2011 (English)In: Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China  (ISKE2011), 2011, 485-494 p.Conference paper, Published paper (Refereed)
Abstract [en]

Automatic speech recognition (ASR) often fails in acoustically noisy environments. Aimed to improve speech recognition scores of an ASR in a real-life like acoustical environment, a speech pre-processing system is proposed in this paper, which consists of several stages: First, a convolutive blind source separation (BSS) is applied to the spectrogram of the signals that are pre-processed by binaural Wiener filtering (BWF). Secondly, the target speech is detected by an ASR system recognition rate based on a Hidden Markov Model (HMM). To evaluate the performance of the proposed algorithm, the signal-to-interference ratio (SIR), the improvement signal-to-noise ratio (ISNR) and the speech recognition rates of the output signals were calculated using the signal corpus of the CHiME database. The results show an improvement in SIR and ISNR, but no obvious improvement of speech recognition scores. Improvements for future research are suggested.

Place, publisher, year, edition, pages
2011. 485-494 p.
Series
Advances in Intelligent and Soft Computing, ISSN 1867-5662 ; 124
Keyword [en]
ASR, BSS, BWF, Automatic speech recognition, Convolutive blind source separation, Noisy environment, Output signal, Pre-processing, Recognition rates, Signal to noise, Signal-to-interference ratio, Spectrograms, Target speech, Wiener filtering, WIENER filters, Blind source separation, Hidden Markov models, Intelligent systems, Knowledge engineering, Separation, Signal to noise ratio, Speech communication, Speech enhancement, Speech recognition
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-150662DOI: 10.1007/978-3-642-25658-5_58ISI: 000307258900058Scopus ID: 2-s2.0-84855232635ISBN: 9783642256578 (print)OAI: oai:DiVA.org:kth-150662DiVA: diva2:745937
Conference
Sixth International Conference on Intelligent Systems and Knowledge Engineering (ISKE2011), Shanghai, China, December 15–17, 2011
Projects
AUDIS
Funder
EU, European Research Council
Note

QC 20140911

Available from: 2014-09-11 Created: 2014-09-08 Last updated: 2017-03-24Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf