Skip to main content
SpringerLink
Log in

Endpoint Detection of Isolated Korean Utterances for Bimodal Speech Recognition in Acoustic Noisy Environments

  • Conference paper
Foundations of Intelligent Systems (ISMIS 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2871))

Included in the following conference series:

  • 493 Accesses

Abstract

This paper proposes a reliable endpoint detection method for a bimodal system in an acoustically noisy environment. Endpoints are detected in the audio and video signals, and then suitable ones are selected depending on the signal-to-noise ratio (SNR) estimated in the input audio signal. Experimental results show that the proposed method can significantly reduce a detection error rate and produce acceptable recognition accuracy in a bimodal system, even with a very low SNR.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Teissier, P., Ribes, J.R., Schwartz, J.-L., Dugue, A.G.: Comparing Models for Audiovisual Fusion in a Noisy-Vowel Recognition Task. IEEE Trans. Speech Audio Processing 7(6), 629–642 (1999)

    Article  Google Scholar 

  2. Bregler, C., Konig, Y.: Eigenlips for Robust Speech Recognition. In: Proc. IEEE ICASSP 1994, vol. (2), pp. 669–672 (1994)

    Google Scholar 

  3. Chen, T.: Audiovisual Speech Processing: Lip Reading and Lip Synchronization. IEEE Signal Processing Mag. 18(1), 9–21 (2001)

    Article  MATH  Google Scholar 

  4. Oh, H.-H., Jeoun, Y.-M., Chien, S.-I.: A Set of Mesh Features for Automatic Visual Speech Recognition. In: Proc. IARP MVA 2002, pp. 488–491 (2002)

    Google Scholar 

  5. Matthews, I., Cootes, T.F., Bangham, J.A., Cox, S., Harvey, R.: Extraction of Visual Features for Lipreadig. IEEE Trans. Pattern Anal. Machine Intell. 24(2), 198–213 (2002)

    Article  Google Scholar 

  6. Rabiner, L.R., Sambur, M.R.: An Algorithm for Determining the Endpoints of Isolated Uttrances. Bell Syst. Tech. J. 54(2), 297–315 (1975)

    Google Scholar 

  7. Lamel, L.F., Rabiner, L.R., Rosenberg, A.E., Wilpon, J.G.: An Improved Endpoint Detector for Isolated Word Recognition. IEEE Trans. Acoust., Speech, Signal Processing ASSP 29(4), 777–785 (1981)

    Article  Google Scholar 

  8. Ying, G.S., Mitchell, C.D., Jamieson, L.H.: Endpoint Detection of Isolated Utterances Based on a Modified Teager Energy Measurement. In: Proc. IEEE ICASSP 1993, pp. 732–735 (1993)

    Google Scholar 

  9. Haigh, J.A., Mason, J.S.: Robust Voice Activity Detection Using Cepstral Features. In: Proc. IEEE TENCON 1999, pp. 321–324 (1999)

    Google Scholar 

  10. Tanyer, S.G., Özer, H.: Voice Activity Detection in Nonstationary Noise. IEEE Trans. Speech Audio Processing 8, 478–482 (2000)

    Article  Google Scholar 

  11. Kwon, H.-S., Son, J.-M., Jung, S.-Y., Bae, K.-S.: Speech Enhancement Using Microphone Array with MMSE-STSA Based Post-Processing. In: Proc. ICEIC 2002, pp. 186–189 (2002)

    Google Scholar 

  12. Bou-Ghazale, S., Assaleh, K.: A Robust Endpoint Detection of Speech for Noisy Environments with Application to Automatic Speech Recognition. In: Proc. IEEE ICASSP 2002, pp. IV-3808–IV-3811 (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, 702-701, Korea

    Hyun-Hwa Oh, Hong-Seok Kwon, Jong-Mok Son, Keun-Sung Bae & Sung-Il Chien

Authors
  1. Hyun-Hwa Oh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hong-Seok Kwon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jong-Mok Son
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Keun-Sung Bae
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sung-Il Chien
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. The International WIC Institute, Beijing University of Technology, China

    Ning Zhong

  2. Department of Computer Science, University of North Carolina, NC 28223, Charlotte, USA

    Zbigniew W. Raś

  3. Shimane University, 89-1 Enya-cho Izumo, 6938501, Shimane, Japan

    Shusaku Tsumoto

  4. Department of Informatics, Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi, 819-0395, Fukuoka, Japan

    Einoshin Suzuki

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Oh, HH., Kwon, HS., Son, JM., Bae, KS., Chien, SI. (2003). Endpoint Detection of Isolated Korean Utterances for Bimodal Speech Recognition in Acoustic Noisy Environments. In: Zhong, N., Raś, Z.W., Tsumoto, S., Suzuki, E. (eds) Foundations of Intelligent Systems. ISMIS 2003. Lecture Notes in Computer Science(), vol 2871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39592-8_82

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-39592-8_82

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20256-1

  • Online ISBN: 978-3-540-39592-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation