297
Views
2
CrossRef citations to date
0
Altmetric
Research Article

Evaluation of model-based versus non-parametric monaural noise-reduction approaches for hearing aids

, &
Pages 627-639 | Received 02 Aug 2011, Accepted 07 Apr 2012, Published online: 30 May 2012

References

  • Beerends J.G., Hekstra A.P., Rix A.W. & Hollier M.P. 2002. Perceptual evaluation of speech quality (PESQ): The New ITU standard for end-to-end speech quality assessment Part II. Psychoacoustic model. Journal of the Audio Engineering Society, 50(10), 765–778.
  • Breithaupt C., Gerkmann T. & Martin R. 2008. A novel a priori SNR estimation approach based on selective cepstro-temporal smoothing. IEEE International Conference on Acoustics, Speech and Signal Processing 2008. 4897–4900.
  • Bentler R. & Chiou L. 2006. Digital noise reduction: An overview. Trends in Amplification, 10(2), 67–82.
  • Bortz J., Lienert G. & Boehnke K. 2000. Verteilungsfreie Methoden in der Biostatistik. Heidelberg, Germany: Springer Verlag.
  • Boymanns M. & Dreschler W.A. 2000. Field trials using a digital hearing aid with active noise reduction and dual-microphone directionality. Int J Audiol, 39(5), 260–268.
  • Cappé O. 1994. Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor. IEEE Trans Speech Audio Process, 2(2), 345–359.
  • Chan D., Fourcin A., Gibbon D., Granstrom B., Huckvale M. . 1995. EUROM - A spoken language resource for the EU. Proc. Eurospeech, 1, 867–870.
  • Cohen I. & Berdugo B. 2002. Noise estimation by minima controlled recursive averaging for robust speech enhancement. IEEE Signal Process Lett, 9, 12–15.
  • Dau T., Püschel D. & Kohlrausch A. 1996. A quantitative model of the “effective” signal processing in the auditory system: I. model structure. J Acoust Soc Am, 99, 3615–3622.
  • Dreschler W., Verschuure H., Ludvigsen C. & Westermann S. 2001. ICRA noises: artificial noise signals with speech-like spectral and temporal properties for hearing instrument assessment. International Collegium for Rehabilitative Audiology. Int J Audiol, 40(3), 148–157. http://www.icra.nu/.
  • Emiya V., Vincent E., Harlander N. & Hohmann V. 2011. Subjective and objective quality assessment of audio source separation. IEEE Trans Speech Audio Process, 19(7), 2046–2057.
  • Eneman K., Luts H., Wouters J., Büchler M., Dillier N. . 2008. Evaluation of signal enhancement algorithms for hearing instruments. 16th European Signal Processing Conference (EUSIPCO).
  • Ephraim Y. & Malah D. 1984. Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator. IEEE Trans Speech Audio Process, ASSP-32(6), 1109–1121.
  • Ephraim Y. & Malah D. 1985. Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator. IEEE Trans Speech Audio Process, ASSP-33(2), 443–445.
  • Ephraim Y. 1992. Statistical model based speech enhancement systems. IEEE Proc, 80(10), 1526–1555.
  • Ephraim Y. & Van Trees H.L. 1995. A signal subspace approach for speech enhancement. IEEE Trans Speech Audio Process, 3, 251–266.
  • Fredelake S. & Holube I. 2010. Quality judgement by paired comparison. Z Audiol, 49(4), 149–156.
  • Garofolo J.S., Lamel L.F., Fisher W.M. Fiscus J.G., Pallett D.S. . 1993. TIMIT Acoustic-phonetic continuous speech corpus. Massachusetts Institute of Technology (MIT), SRI International (SRI) and Texas Instruments, Inc. (TI), Linguistic Data Consortium, Philadelphia.
  • Gramß T. & Strube H.W. 1990. Recognition of isolated words based on psychoacoustics and neurobiology. Speech Communication, 9, 35–40.
  • Gribonval R., Benaroya L., Vincent E. & Févotte C. 2003. Proposals for performance measurement in source separation. Proc. 5th International Conference on Independent Component Analysis and Blind Signal Separation (ICA).
  • Griffin D. & Lim J. 1984. Signal estimation from modified short-time Fourier transform. IEEE Trans Speech Audio Process, 32(2), 236–243.
  • Grimm G., Herzke T., Berg D. & Hohmann V. 2006. The master hearing aid: A PC-based platform for algorithm development and evaluation. Acta Acustica united with Acustica, 92,618–628.
  • Harlander N., Rohdenburg T. & Hohmann, V. Single-channel noise suppression based on a statistical source-model for speech. In: T. Dau, J. Buchholz, J. Harte, T. Christiansen (eds.). Auditory Signal Processing in Hearing-Impaired Listeners (International Symposium on Auditory and Audiological Research), Brøndby, DK: Centertryk A/S, pp. 433–440.
  • Hirsch H.-G. & Ehrlicher C. 1995. Noise estimation techniques for robust speech recognition. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 153–146.
  • HearCom. Schulte, M (ed.). 2008. Deliverable D-7 - 4: Report tests for listening effort. FP6–004171 HearCom: Hearing in the Communication Society, 1–24.
  • Hu Y. & Loizou P. 2003. A generalized subspace approach for enhancing speech corrupted by colored noise. IEEE Trans. Speech Audio Process, 11(4), 334–341.
  • Hu Y. & Loizou, P. 2007. A comparative intelligibility study of single-microphone noise reduction algorithms. J Acous Soc Am, 122(3), 1777–1786.
  • Hu Y. & Loizou P. 2008. Evaluation of objective quality measures for speech enhancement. IEEE Transactions on Speech and Audio Processing, 16(1), 229–238.
  • Kang G.S. & Fransen L.J. 1989. Quality improvement of LPC-processed noisy speech by using spectral subtraction. IEEE Trans Acoust Speech Signal Processing, 37(6), 930–942.
  • Kim G. & Loizou P. 2010. Improving speech intelligibility in noise using environment-optimized algorithms. IEEE Trans Speech Audio Process, in press.
  • Kim G., Lu Y., Hu Y. & Loizou P. 2009. An algorithm that improves speech intelligibility in noise for normal-hearing listeners. J Acoust Soc Am, 126(3), 1486–149.
  • Kleinschmidt M. & Hohmann V. 2003. Sub-band SNR estimation using auditory feature processing. Speech Communication, 39(1–2), 47–64.
  • Kollmeier B. & Koch, R. 1994. Speech enhancement based on physiological and psychoacoustical models of modulation perception and binaural interaction. J Acoust Soc Am, 95(3), 1593–1602.
  • Kuropatwinski M. & Kleijn W.B. 2006. Estimation of the short-term predictor parameters of speech under noisy conditions. IEEE Trans Speech Audio Process, 14(5), 1645–1655.
  • Lim J.S. 1986. Speech enhancement. Proc IEEE Int Conf Acoustics Speech Signal Processing (ICASSP), 11, 3135–3142.
  • Loizou P.C. (ed.) 2007. Speech Enhancement: Theory and Practice. Boca Raton, USA: CRC Taylor and Francis Group.
  • Luts H., Eneman K., Wouters J., Schulte M, Vormann M. . 2010. Multicenter evaluation of signal enhancement algorithms for hearing aids. J Acoust Soc Am, 127(3), 1570–1583.
  • Martin R., Malah D., Cox R.V. & Accardi A.J. 2004. A noise reduction preprocessor for mobile voice communication. EURASIP. Journal on Applied Signal Processing, 8, 1046–1058.
  • Martin R. 2006. Bias compensation methods for minimum statistics noise power spectral density estimation. IEEE Trans Acoust Speech Signal Processing, 86(6), 1215–1229.
  • Martin R. 2001. Noise power spectral density estimation based on optimal smoothing and minimum statistics. IEEE Trans Speech Audio Process, 9(5), 504–512.
  • Martin R. 1994. Spectral subtraction based on minimum statistics. Proc European Signal Processing Conference, 1, 1182–1185.
  • Marzinzik M. & Kollmeier B. 2001. A review of the Ephraim-Malah noise reduction algorithms. Zeitschrift für Audiologie/Audiological Acoustics, 40(1), 4–15.
  • Marzinzik M. & Kollmeier B. 2002. Speech pause detection for noise spectrum estimation by tracking power envelope dynamics. IEEE Trans Speech Audio Process, 10(2),109–118.
  • Mauler D. & Martin R. 2006. Noise power spectral density estimation on highly correlated data. Proc of International Workshop on Acoustic Echo and Noise Control (IWAENC), 12–14.
  • Nabney I.T. (ed.) 2004. NETLAB. Algorithms for Pattern Recognition (3rd edition). Berlin, Germany: Springer Verlag.
  • Plomp R. 1978. Auditory handicap of hearing impairment and the limited benefit of hearing aids. J Acoust Soc Am, 63, 533–549.
  • Rangachari S. & Loizou P.C. 2006. A noise-estimation algorithm for highly non-stationary environments. Speech Communication, 48, 220–231.
  • Rohdenburg T. 2008. Development and Objective Perceptual Quality Assessment of Monaural and Binaural Noise Reduction Schemes for Hearing Aids. PhD thesis, Carl-von-Ossietzky-Universityt Oldenburg.
  • Rosenkranz T. 2010. Noise Codebook Adaptation for Codebook-Based Noise Reduction. Proc. of International Workshop on Acoustic Echo and Noise Control (IWAENC), Tel Aviv.
  • Rosenkranz T. & Puder H. 2011. Improving robustness of codebook-based noise estimation approaches with delta codebooks. IEEE Trans Audio Speech Language Processing. DOI: 10.1109/TASL.2011.2172943.
  • Rosenkranz T. & Puder H. 2012. Integrating recursive minimum tracking and codebook-based noise estimation for improved reduction of non-stationary noise. Signal Processing, 92, 3, 767–779.
  • Shimamura T. & Kobayashi H. 2001. Weighted autocorrelation for pitch extraction of noisy speech. IEEE Trans Speech Audio Process, 9(7), 727–730.
  • Smits C. & Houtgast T. 2007. Recognition of digits in different types of noise by normal-hearing and hearing-impaired listeners. Int J Audiol, 46(3), 134–144. http://www.icra.nu/.
  • Srinivasan S. Samuelsson J. & Kleijn W.B. 2006. Codebook driven short-term predictor parameter estimation for speech enhancement. IEEE Trans Speech Audio Process, 14(1), 163–176.
  • Srinivasan S. Samuelsson J. & Kleijn W.B. 2007. Codebook-based Bayesian speech enhancement for nonstationary environments. IEEE Trans Speech Audio Process, 15(2), 441–452.
  • Tchorz J., Kollmeier B. 2003. SNR estimation based on amplitude modulation analysis with applications to noise surppression. IEEE Trans. Speech Audio Process, 11(3), 184–192.
  • Van Eyken, E., Van Camp, G. & Van Laer L. 2007. The complexity of age-related hearing impairment: Contributing environmental and genetic factors. Audiol Neurotol, 12, 345–358.
  • Van Gerven S. & Xie F. 1997. A Comparative Study of Speech Detection Methods. EUROSPEECH ‘97 5th European Conference on Speech Communication, Technology, pp. 1095–1098.
  • Varga A., Steeneken H., Tomlinson M. & Jones D. 1992. The NOISEX-92 study on the effect of additive noise on automatic speaker recognition. Technical report, Speech Research Unit, Defence Research Agency, Malvern, UK.
  • Vary P., Heute U. & Hess W. 1998. Digitale Sprachsignalverarbeitung (1. edition). Stuttgart, Germany: Teubner Verlag.
  • Virag N. 1999. Single channel speech enhancement based on masking properties of the human auditory system. IEEE Trans. Speech Audio Process, 7(2), 126–137.
  • Wagener K., Kühnel T. & Kollmeier B. 1999. Entwicklung und Evaluation eines Satztests für die deutsche Sprache I: Design des Oldenburger Satztests. Zeitschrift für Audiologie/Audiological Acoustics, 38(1), 4–15.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.