Advertisement

Automatic Live Monitoring of Communication Quality for Normal-Hearing and Hearing-Impaired Listeners

  • Jan Rennies
  • Eugen Albertin
  • Stefan Goetze
  • Jens-E. Appell
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6180)

Abstract

This contribution presents a system, which allows for a continuous monitoring of speech intelligibility from a single microphone signal. The system accounts for the detrimental effects of environmental noise and reverberation by estimating the two relevant parameters signal-to-noise ratio and reverberation time, and feeding them to a speech intelligibility model. Due to its real-time functionality and the fact that no reference signal is required, the system offers a wide range of opportunities to monitor communication channels and control further signal enhancement mechanisms. A priori knowledge of the individual hearing loss can be used to make the system applicable also for hearing-impaired users.

Keywords

Hearing Loss Hearing Impairment Modulation Transfer Function Communication Quality Speech Intelligibility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ephraim, Y., Malah, D.: Speech enhancement using a minimum mean–square error log-spectral amplitude estimator. IEEE Transaction on Acoustics, Speech and Signal Processing 33(2), 443–445 (1985)CrossRefGoogle Scholar
  2. 2.
    Marzinzik, M., Kollmeier, B.: Speech pause detection for noise spectrum estimation by tracking power envelope dynamics. IEEE Transactions on Speech and Audio Processing 10(2), 109–118 (2002)CrossRefGoogle Scholar
  3. 3.
    Habets, E.: Single and Multi-Microphone Speech Dereverberation using Spectral Enhancement. PhD thesis, University of Eindhoven, Eindhoven, The Netherlands (June 2007)Google Scholar
  4. 4.
    Houtgast, T., Steeneken, H.: A review of the MTF concept in room acoustics and its use for estimating speech intelligibility in auditoria. J. Acoust. Soc. Am. 77, 1069–1077 (1985)CrossRefGoogle Scholar
  5. 5.
    International Electrotechnical Commission: IEC 60268-16 Sound System Equipment - Part 16: Objective rating of speech intelligibility by speech transmission index (1998)Google Scholar
  6. 6.
    Fletcher, H., Galt, R.: The perception of speech and its relation to telephony. J. Acoust. Soc. Am. 22, 89–151 (1950)CrossRefGoogle Scholar
  7. 7.
    Schröder, J., Rohdenburg, T., Hohmann, V., Ewert, S.D.: Classification of reverberant acoustic situations. In: Boone, M. (ed.) Proceedings of the International Conference on Acoustics NAG/DAGA 2009, pp. 606–609. DEGA e.V, Berlin (2009)Google Scholar
  8. 8.
    Holube, I., Kollmeier, B.: Speech intelligibility prediction in hearing-impaired listeners based on a psychoacoustically motivated perception model. J. Acoust. Soc. Am. 100, 1703–1716 (1996)CrossRefGoogle Scholar
  9. 9.
    Wagener, K., Brand, T., Kollmeier, B.: Development and Evaluation of a German Sentence Test. In: Contributions to Psychological Acoustics - 8th Oldenburg Symposium on Psychological Acoustics, pp. 439–466. bis-Verlag, Oldenburg (2000)Google Scholar
  10. 10.
    American National Standards Institute: ANSI S3.5-1997 Methods for calculation of the speech intelligibility index (1997)Google Scholar
  11. 11.
    Tchorz, J., Kollmeier, B.: SNR estimation based on amplitude modulation analysis with applications to noise suppression. IEEE Transactions on Speech and Audio Processing 11(3), 184–192 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jan Rennies
    • 1
  • Eugen Albertin
    • 1
  • Stefan Goetze
    • 1
  • Jens-E. Appell
    • 1
  1. 1.Fraunhofer IDMT, Hearing, Speech and Audio TechnologyOldenburgGermany

Personalised recommendations