Skip to main content
Log in

Pitch-Based Voice Activity Detection for Feedback Cancellation and Noise Reduction in Hearing Aids

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

In hearing aid (HA) systems, amplification of speech signals is done to compensate the hearing loss of patients. Background noise and feedback signals may also get amplified which degrade the intelligibility and quality of speech. To achieve high de-noise efficiency, signal processing unit in HA system has voice activity detector (VAD). The conventional VAD detects voice based on zero crossing rate or energy of input signals. However, these methods cannot perform well at low SNR or non-stationary noise environments. Since pitch is a special characteristic of speech and is basically independent of noise intensity, VAD based on pitch can have high accuracy even when the noise spectrum is changing drastically. In this paper, pitch-based VAD is presented and its accuracy is checked against zero crossing rate-based VAD (ZCR-VAD). For noise reduction, an improved multi-band spectral over-subtraction algorithm is employed along with the high accurate pitch-based VAD. For feedback cancellation, the performance of adaptive algorithms like NLMS, RLS and affine projection (AP) algorithms with pitch-based VAD is compared and it is observed that AP is suitable for feedback cancellation. The proposed noise reduction and feedback cancellation algorithm with pitch-based VAD method is tested with NOIZEUS speech database and with real-time noisy speech signals. The simulation results show that the accuracy of pitch-VAD is about 23% higher than that of ZCR-VAD. The SNR for the proposed noise reduction and feedback cancellation with pitch-VAD method is improved by 10 dB than conventional spectral subtraction and adaptive algorithms. Mean opinion score (MOS) obtained for the proposed method is 4.3 out of 5.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Y.J. Chen, C.W. Wei, Y. FanChiang, Y.L. Meng, Y.C. Huang, S.J. Jou, Neuromorphic pitch based noise reduction for monosyllable hearing aid system application. IEEE Trans. Circuits Syst. I 61(2), 463–475 (2014)

    Article  Google Scholar 

  2. Y.J. Chen, C.W. Wei, Y.L. Meng, S.J. Jou, Low computational complexity pitch based VAD for dynamic environment in hearing aids. ICCIC, Part V, CCIS 235, 10–17 (2011)

    Google Scholar 

  3. Y.F. Chiang, C.W. Wei, Y.L. Meng, Y.W. Lin, S.J. Jou, Low complexity formant estimation adaptive feedback cancellation for hearing aids using pitch based processing. IEEE/ACM Trans. Audio Speech Lang. Process. 22(8), 1248–1259 (2014)

    Article  Google Scholar 

  4. R. Chinaboina, D.S. Ramkiran, Adaptive algorithms for acoustic echo cancellation in speech processing. Int. J. Res. Rev. Appl. Sci. 7(1), 38–42 (2011)

    Google Scholar 

  5. Y. Ephraim, D. Malah, Speech enhancement using a minimum mean-square error log-spectral amplitude estimator. Proc. IEEE Trans. Acoust. Speech Signal Process. 33(2), 443–445 (1985)

    Article  Google Scholar 

  6. P.K. Ghosh, A. Tsiartas, S. Narayanan, Robust voice activity detection using long term signal variability. Proc. IEEE Trans. Audio Speech Lang. Process. 19(3), 600–613 (2011)

    Article  Google Scholar 

  7. Y. Hu, P.C. Loizou, A generalized subspace approach for enhancing speech corrupted by colored noise. IEEE Trans. Speech Audio Process. 11(4), 334–341 (2003)

    Article  Google Scholar 

  8. http://ecs.utdallas.edu/loizou/speech/noizeus/

  9. http://kom.aau.dk/group/04gr742/pdf/framing_worksheet.pdf

  10. M. Karam, H.F. Khazaal, H. Aglan, C. Cole, Noise removal in speech processing using spectral subtraction. J. Signal Inf. Process. 5(02), 32–41 (2014)

    Google Scholar 

  11. Y.T. Kuo, T.J. Lin, Y.T. Li, C.W. Liu, Design and implementation of low-power ANSI S1.11 filter bank for digital hearing aids. IEEE Trans. Circuits Syst. I 57(7), 1684–1696 (2010)

    Article  MathSciNet  Google Scholar 

  12. N.N. Lokhande, N.S. Nehe, P.S. Vikhe, Voice activity detection algorithm for speech recognition applications. in Proceedings of International Journal of Computer Applications (2011)

  13. P. Nagaraju, M. Prakash, Comparative study of different adaptive filter algorithms used for effective noise cancellation. Int. J. Eng. Res. Technol. 3(4) (2014) (ISSN: 2278-0181)

  14. J. Ramírez, J.M. Górriz, J.C. Segura, Voice activity detection. Fundamentals and Speech Recognition System Robustness, ISBN 987-3-90213-08-0, p. 460 (2007)

  15. S.A. Samad, A. Hussain, Development of a voice activity controlled noise canceller. Sensors 12, 6727–6745 (2012)

    Article  Google Scholar 

  16. D.S. Shete, S.B. Patil, Zero crossing rate and energy of the speech signal of devanagari script. IOSR J. VLSI Signal Process. 4(1), 1–5 (2014)

    Article  Google Scholar 

  17. Specification for Octave-Band and Fractional-Octave-Band Analog and Digital Filters, ANSI S1.11-2004, Standards Secretariat Acoustical Society of America (2004)

  18. N. Upadhyay, A. Karmakar, An Improved Multi-Band Spectral Subtraction for Enhancing Speech Degraded by Non-Stationary Noises (Elsevier Publications, Amsterdam, 2013), pp. 39–50

    Google Scholar 

  19. E. Verteletskaya, B. Simak, Noise reduction based on modified spectral subtraction method. IAENG Int. J. Comput. Sci. 38, 1 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Meeradevi Thiagarajan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thiagarajan, M., Natarajan, J. & Sharavanaraju, K.M. Pitch-Based Voice Activity Detection for Feedback Cancellation and Noise Reduction in Hearing Aids. Circuits Syst Signal Process 37, 4504–4526 (2018). https://doi.org/10.1007/s00034-018-0776-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-018-0776-x

Keywords

Navigation