Skip to main content

Blind Estimation of Spectral Standard Deviation from Room Impulse Response for Reverberation Level Recognition Based on Linear Prediction

  • Conference paper
  • First Online:
Digital TV and Wireless Multimedia Communication (IFTC 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 685))

Abstract

Reverberation is an important factor affecting speech quality and intelligibility, Reverberation Time (RT) and Direct-to-Reverberant Ratio (DRR) are the primary parameters for reverberation strength judgement, spectral standard deviation (SSD) from room impulse response (RIR) and DRR exist as monotonic relationships to some extent which means that SSD can also be an indicator of reverberation characteristics. We propose a blind estimation of spectral standard deviation (BESSD) that is obtained directly from reverberant speech signals. Experiments prove BESSD can be used as an index for male reverberation level recognition.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Allen, J.B., Berkley, D.A.: Image method for efficiently simulating small-room acoustics. J. Acoust. Soc. Am. 65(4), 943–950 (1979). Acoustical Society of America

    Article  Google Scholar 

  2. Jeub, M., Nelke, C., Beaugeant, C., Vary, P.: Blind estimation of the coherent-to-diffuse energy ratio from noisy speech signals. In: 2011 19th European Signal Processing Conference, pp. 1347–1351. IEEE (2011)

    Google Scholar 

  3. Lehmann, E.A., Johansson, A.M., Nordholm, S.: Reverberation-time prediction method for room impulse responses simulated with the image-source model. In: 2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp. 159–162. IEEE (2007)

    Google Scholar 

  4. Ikram, M.Z., Morgan, D.R.: A Multiresolution approach to blind separation of speech signals in a reverberant environment. In: Proceedings of the 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2001), vol. 5, pp. 2757–2760. IEEE (2001)

    Google Scholar 

  5. Radlovic, B.D., Williamson, R.C., Kennedy, R.A.: Equalization in an acoustic reverberant environment: robustness results. IEEE Trans. Speech Audio Process. 8(3), 311–319 (2000). IEEE

    Article  Google Scholar 

  6. Lehmann, E.A., Johansson, A.M.: Particle filter with integrated voice activity detection for acoustic source tracking. EURASIP J. Adv. Sig. Process. 2007(1), 1–11 (2006). Springer

    Article  Google Scholar 

  7. Aarabi, P., Shi, G.: Phase-based dual-microphone robust speech enhancement. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 34(4), 1763–1773 (2004). IEEE

    Article  Google Scholar 

  8. Palomäki, K.J., Brown, G.J., Wang, D.: A binaural processor for missing data speech recognition in the presence of noise and small-room reverberation. Speech Commun. 43(4), 361–378 (2004). Elsevier

    Article  Google Scholar 

  9. Joyce, W.B.: Sabine’s reverberation time and ergodic auditoriums. J. Acoust. Soc. Am. 58(3), 643–655 (1975). Acoustical Society of America

    Article  Google Scholar 

  10. Eaton, J., Moore, A.H., Naylor, P.A., Skoglund, J.: Direct-to-reverberant ratio estimation using a null-steered beamformer. In: 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 46–50. IEEE (2015)

    Google Scholar 

  11. Falk, T.H., Chan, W.-Y.: Temporal dynamics for blind measurement of room acoustical parameters. IEEE Trans. Instrum. Meas. 59(4), 978–989 (2010). IEEE

    Article  Google Scholar 

  12. Gillespie, B.W., Malvar, H.S., Florêncio, D.A.F.: Speech dereverberation via maximum-kurtosis subband adaptive filtering. In: Proceedings of the 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2001), vol. 6, pp. 3701–3704. IEEE (2001)

    Google Scholar 

  13. Gaubitch, N.D., Ward, D.B., Naylor, P.A.: Statistical analysis of the autoregressive modeling of reverberant speech. J. Acoust. Soc. Am. 120(6), 4031–4039 (2006). Acoustical Society of America

    Article  Google Scholar 

  14. Yegnanarayana, B., Murthy, P.S.: Enhancement of reverberant speech using LP residual signal. IEEE Trans. Speech Audio Process. 8(3), 267–281 (2000). IEEE

    Article  Google Scholar 

  15. Vaidyanathan, P.P.: The theory of linear prediction. Synth. Lect. Sig. Process. 2(1), 1–184 (2007). Morgan & Claypool Publishers

    Google Scholar 

  16. Peterson, G.E., Barney, H.L.: Control methods used in a study of the vowels. J. Acoust. Soc. Am. 24(2), 175–184 (1952). Acoustical Society of America

    Article  Google Scholar 

  17. Habets, E.A.P., Gannot, S., Cohen, I.: Late reverberant spectral variance estimation based on a statistical model. IEEE Sig. Process. Lett. 16(9), 770–773 (2009). IEEE

    Article  Google Scholar 

  18. Jetzt, J.J.: Critical distance measurement of rooms from the sound energy spectral response. J. Acoust. Soc. Am. 65(5), 1204–1211 (1979). Acoustical Society of America

    Article  Google Scholar 

Download references

Acknowledgments

The authors thank Prof. W.-Y. Chan for his guidance, assistance and support for this research.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Sai Ma or Xi Xie .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Nature Singapore Pte Ltd.

About this paper

Cite this paper

Ma, S., Xie, X. (2017). Blind Estimation of Spectral Standard Deviation from Room Impulse Response for Reverberation Level Recognition Based on Linear Prediction. In: Yang, X., Zhai, G. (eds) Digital TV and Wireless Multimedia Communication. IFTC 2016. Communications in Computer and Information Science, vol 685. Springer, Singapore. https://doi.org/10.1007/978-981-10-4211-9_23

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-4211-9_23

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4210-2

  • Online ISBN: 978-981-10-4211-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics