Hearing impairment is the number one chronic
disability affecting many people in the world. Background noise is
particularly damaging to speech intelligibility for people with
hearing loss especially for sensorineural loss patients. Several
investigations on speech intelligibility have demonstrated
sensorineural loss patients need 5-15 dB higher SNR than the normal
hearing subjects. This paper describes Discrete Hartley Transform
Power Normalized Least Mean Square algorithm (DHT-LMS) to
improve the SNR and to reduce the convergence rate of the Least
Means Square (LMS) for sensorineural loss patients. The DHT
transforms n real numbers to n real numbers, and has the convenient
property of being its own inverse. It can be effectively used for noise
cancellation with less convergence time. The simulated result shows
the superior characteristics by improving the SNR at least 9 dB for
input SNR with zero dB and faster convergence rate (eigenvalue ratio
12) compare to time domain method and DFT-LMS.
[1] Shaul Florian and Neil J Bershad. " A Weighted Normalized Frequency
Domain LMS Adaptive Algorithm". IEEE Transactions on Acoustics
speech and signal processing., Vol. 36, no. 7, July 1998
[2] Francosie Beaufays. " Trasnform domain adaptive filters: An analytical
approach". IEEE Transactions on Signal processing, vol. 43, no. 2, Feb
1995
[3] Mohammed A Shamma. " Improving the speed and performance of
adaptive equalizers via transform based adaptive filtering ". 2591
Ashurst Rd. University Heights, Ohio, 44118, USA.
[4] Adaptive filter theory. By Simon Haykin.
[5] V.Udayashankara, A.P.Shivaprasad., " Digital Hearing Aid: A Review".
World
congress on Medical physics & Biomedical Engineering. Brejil, Aug.
1994. Pp. 21-26.
[6] V.Udayashankara , A.P.Shivaprasad. " The application of voltera LMS
Adaptive filtering to speech enhancement for the Hearing Impairment ".
4th Euro-speech conference on speech communication and Technology,
Mandrid, Spain. Sept.1995. pp. 18-21.
[7] Moore. B.C., Stainsby. T.H., Alcantara. J.I., Kuhnel. V., "The effect of
speech intelligibility of varying compression time constants in a digital
hearing aid". International Journal on Audio logy. 2004 Jul-Aug: 43(7),
pp. 399-409.
[8] Chung.K., "Challenges and recent developments in Hearing Aids".,
Trends Amplif.2004:8(3). Pp. 83-124.
[9] Shanks. J.E., Wilson. R.H.Larson, Williams. D., " Speech recognition
performance of patients with sensorineural hearing loss under unaided
and aided conditions using linear and compression hearing aids". Ear
hear. 2002 Aug: 23(4), pp. 280-90.
[10] Baer.T., Moore.B.C., Kulk.K., " Effects of low pass filtering on the
intelligibility of speech in noise for people with and without dead
regions at high frequencies". Journal on Acoustic soc Am. 2002 Sept:
112(3 pt 1)., pp. 1133-44.
[11] Hornsby.B.W. Ricketts.T.A., "The effects of compression ratio, signalto-
noise ratio and level on speech recognition in normal-hearing
listners". Journal on Acoustics soc Am. 2001 June: 109(6). pp. 2964-
73.
[12] Shields.P.W., Campbell.B.R., " Improvements in intelligibility of noisy
reverberant speech using a binaural sub band adaptive noise-cancellation
processing scheme". Journal on Acoustics Soc Am. 2001Dec: 110(6).
Pp. 3232-42.
[13] Wouters.J., Litiere.L., Van Wieringen.A., " Speech intelligibility in
noisy environment with one and two microphone hearing aids".
Audiology. 1999 Mar-Apr: 38(2). Pp 91-8.
[14] Rankovic.C.M., " Factors governing speech reception benefits of
adaptive linear filtering for listeners with sensorineural loss". Jpurnal on
Acoustics Soc Am. 1998 Feb: 103(2). Pp. 1043-57.
[15] Baer. T., Moore.B.C., Gatechouse. S., "Spectral contrast enhancement
of speech in noise for listeners with sensorineural hearing impairment:
effects on intelligibility, quality, and response times". Journal on
Rehabilitation Res Dev. 1993:30(1). Pp.. 49-72.
[16] Dr. Harry Levitt, " Noise reduction in Hearing aids: An overview ".
Journal of Rehabilitation Research and Development, Vol.38. No.1, Jan-
2001.
[17] Sunitha S.L and Dr.V Udayashankara, " DFT-LMS Speech
Enhancement Technique for Sensorinueural loss Patients". Journal of
Bioinformatics India, Vol 3. Jan-March 2005.
[18] Simon Haykin, Adaptive Filter Theory", Pearson Education Asia, 4th
Edition, 2002.
[19] Bernard Widrow and Samuel D.Stearns. " Adaptive Signal Processing",
Pearson Education Asia, 2002.
[20] Sunitha S.L and Dr.V. Udayashankara. " DWT-LMS Speech
Enhancement Technique for Performance Enhancement of Digital
Hearing Aid", ICSCI, Jan 2005. (Best paper of the session has been
taken for this paper)
[1] Shaul Florian and Neil J Bershad. " A Weighted Normalized Frequency
Domain LMS Adaptive Algorithm". IEEE Transactions on Acoustics
speech and signal processing., Vol. 36, no. 7, July 1998
[2] Francosie Beaufays. " Trasnform domain adaptive filters: An analytical
approach". IEEE Transactions on Signal processing, vol. 43, no. 2, Feb
1995
[3] Mohammed A Shamma. " Improving the speed and performance of
adaptive equalizers via transform based adaptive filtering ". 2591
Ashurst Rd. University Heights, Ohio, 44118, USA.
[4] Adaptive filter theory. By Simon Haykin.
[5] V.Udayashankara, A.P.Shivaprasad., " Digital Hearing Aid: A Review".
World
congress on Medical physics & Biomedical Engineering. Brejil, Aug.
1994. Pp. 21-26.
[6] V.Udayashankara , A.P.Shivaprasad. " The application of voltera LMS
Adaptive filtering to speech enhancement for the Hearing Impairment ".
4th Euro-speech conference on speech communication and Technology,
Mandrid, Spain. Sept.1995. pp. 18-21.
[7] Moore. B.C., Stainsby. T.H., Alcantara. J.I., Kuhnel. V., "The effect of
speech intelligibility of varying compression time constants in a digital
hearing aid". International Journal on Audio logy. 2004 Jul-Aug: 43(7),
pp. 399-409.
[8] Chung.K., "Challenges and recent developments in Hearing Aids".,
Trends Amplif.2004:8(3). Pp. 83-124.
[9] Shanks. J.E., Wilson. R.H.Larson, Williams. D., " Speech recognition
performance of patients with sensorineural hearing loss under unaided
and aided conditions using linear and compression hearing aids". Ear
hear. 2002 Aug: 23(4), pp. 280-90.
[10] Baer.T., Moore.B.C., Kulk.K., " Effects of low pass filtering on the
intelligibility of speech in noise for people with and without dead
regions at high frequencies". Journal on Acoustic soc Am. 2002 Sept:
112(3 pt 1)., pp. 1133-44.
[11] Hornsby.B.W. Ricketts.T.A., "The effects of compression ratio, signalto-
noise ratio and level on speech recognition in normal-hearing
listners". Journal on Acoustics soc Am. 2001 June: 109(6). pp. 2964-
73.
[12] Shields.P.W., Campbell.B.R., " Improvements in intelligibility of noisy
reverberant speech using a binaural sub band adaptive noise-cancellation
processing scheme". Journal on Acoustics Soc Am. 2001Dec: 110(6).
Pp. 3232-42.
[13] Wouters.J., Litiere.L., Van Wieringen.A., " Speech intelligibility in
noisy environment with one and two microphone hearing aids".
Audiology. 1999 Mar-Apr: 38(2). Pp 91-8.
[14] Rankovic.C.M., " Factors governing speech reception benefits of
adaptive linear filtering for listeners with sensorineural loss". Jpurnal on
Acoustics Soc Am. 1998 Feb: 103(2). Pp. 1043-57.
[15] Baer. T., Moore.B.C., Gatechouse. S., "Spectral contrast enhancement
of speech in noise for listeners with sensorineural hearing impairment:
effects on intelligibility, quality, and response times". Journal on
Rehabilitation Res Dev. 1993:30(1). Pp.. 49-72.
[16] Dr. Harry Levitt, " Noise reduction in Hearing aids: An overview ".
Journal of Rehabilitation Research and Development, Vol.38. No.1, Jan-
2001.
[17] Sunitha S.L and Dr.V Udayashankara, " DFT-LMS Speech
Enhancement Technique for Sensorinueural loss Patients". Journal of
Bioinformatics India, Vol 3. Jan-March 2005.
[18] Simon Haykin, Adaptive Filter Theory", Pearson Education Asia, 4th
Edition, 2002.
[19] Bernard Widrow and Samuel D.Stearns. " Adaptive Signal Processing",
Pearson Education Asia, 2002.
[20] Sunitha S.L and Dr.V. Udayashankara. " DWT-LMS Speech
Enhancement Technique for Performance Enhancement of Digital
Hearing Aid", ICSCI, Jan 2005. (Best paper of the session has been
taken for this paper)
@article{"International Journal of Medical, Medicine and Health Sciences:58275", author = "Sunitha S. L. and V. Udayashankara", title = "DHT-LMS Algorithm for Sensorineural Loss Patients", abstract = "Hearing impairment is the number one chronic
disability affecting many people in the world. Background noise is
particularly damaging to speech intelligibility for people with
hearing loss especially for sensorineural loss patients. Several
investigations on speech intelligibility have demonstrated
sensorineural loss patients need 5-15 dB higher SNR than the normal
hearing subjects. This paper describes Discrete Hartley Transform
Power Normalized Least Mean Square algorithm (DHT-LMS) to
improve the SNR and to reduce the convergence rate of the Least
Means Square (LMS) for sensorineural loss patients. The DHT
transforms n real numbers to n real numbers, and has the convenient
property of being its own inverse. It can be effectively used for noise
cancellation with less convergence time. The simulated result shows
the superior characteristics by improving the SNR at least 9 dB for
input SNR with zero dB and faster convergence rate (eigenvalue ratio
12) compare to time domain method and DFT-LMS.", keywords = "Hearing Impairment, DHT-LMS, Convergence rate,SNR improvement.", volume = "1", number = "10", pages = "547-4", }
