Since the introduction of the first commercial digital hearing aid in 1996, the possibilities of digital signal processing (DSP) have increasingly been exploited in hearing aids. DSP allows for the implementation of signal processing schemes (i.e., “algorithms”) that have no counterpart in the analog domain and thus offers new, interesting perspectives for the rehabilitation of hearing impairment, only parts of which have been realized to date. This section reviews the processing schemes currently used in digital hearing aids and outlines the main lines of research toward improved processing schemes.
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References
Agnew J and Thornton JM (2000). Just noticeable and objectionable group delays in digital hearing aids. J. Am. Acad. Audiol. 11, 330–336.
Moore BCJ (1995) Perceptual consequences of cochlear damage. Oxford University Press, Oxford.
Kollmeier B (1999) On the four factors involved in sensorineural hearing loss. In: Dau T, Hohmann V and Kollmeier B (Eds): Psychophysics, physiology and models of hearing. World Scientific, Singapore 211–218.
Kollmeier B (Ed) (1996) Psychoacoustics, speech and hearing aids. World Scientific, Singapore.
Dillon H (2001) Hearing aids. Boomerang Press, Turramurra, Australia.
Kates JM (1998) Signal processing for Hearing Aids. In: Kahrs M and Brandenburg K (Eds): Applications of digital signal processing to audio and acoustics. Kluwer, Dordrecht.
Plomp R (1994) Noise, amplification, and compression: Considerations of three main issues in hearing aid design. Ear Hear. 15, 2–12.
Turner C and Henry B (2002) Benefits of amplification for speech recognition in background noise. J. Acoust. Soc. Am. 112, 1675–1680.
Turner CW and Hurtig RR (1999) Proportional frequency compression of speech for listeners with sensorineural hearing loss. J. Acoust. Soc. Am. 106, 877–886.
Sakamoto S, Goto K, Tateno M and Kaga K (2000) Frequency compression hearing aid for severe-to-profound hearing impairments. Auris Nasus Larynx. 27(4), 327–334.
Stone MA, Moore BCJ, Alcantara JI and Glasberg BR (1999) Comparison of different forms of compression using wearable digital hearing aids. J. Acoust. Soc. Am. 106, 3603–3619.
Verschuure J, Maas AJJ, Stikvoort E, de Jong RM, Goedegebure A and Dreschler WA (1996) Compression and its effect on the speech signal. Ear Hear. 17, 162–175.
Jenstad LM, Seewald RC, Cornelisse LE and Shantz J. Comparison of linear gain and wide dynamic range compression hearing aid circuits: Aided speech perception measures. Ear Hear. 20(2), 117–126.
Baer T and Moore BCJ (1994) Spectral enhancement to compensate for reduced frequency selectivity. J. Acoust. Soc. Am. 95, 2992.
Yang J, Luo FL and Nehorai A (2003) Spectral contrast enhancement: Algorithms and comparisons. Speech Commun. 39(1–2), 33–46.
Ephraim Y and Malah D (1985) Speech enhancement using a minimum mean-square error log-spectral amplitude estimator. IEEE Trans. Acoust., Speech, Signal Process. ASSP 33(2), 443–445.
Tchorz J and Kollmeier B (2003) SNR estimation based on amplitude modulation analysis with applications to noise suppression. IEEE Trans. Speech Audio Process. 11(3), 184–192.
Elko GW and Pong A-TN (1995) A simple adaptive first-order differential microphone. IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, NY, USA.
Campbell DR and Shields PW (2003) Speech enhancement using sub-band adaptive Griffiths – Jim signal processing. Speech Commun. 39(1–2), 97–110.
Widrow B and Luo FL (2003) Microphone arrays for hearing aids: An overview. Speech Commun. 39(1–2): 139–146.
Wittkop T and Hohmann V (2003) Strategy-selective noise reduction for binaural digital hearing aids. Speech Commun. 39, 111–138.
Bodden, M (1993) Modeling human sound-source localization and the cocktail-party-effect. Acta Acustica 1, 43–56.
Marzinzik M and Kollmeier B (2003) Predicting the subjective quality of noise reduction algorithms for hearing aids. Acta Acustica/Acustica, 89, 521–529.
Greenberg JE, Zurek PM and Brantley M (2000). Evaluation of feedback-reduction algorithms for hearing aids. J. Acoust. Soc. Am. 108, 2366–2376.
Nordqvist P and Leijon A (2004) An efficient robust sound classification algorithm for hearing aids. J. Acoust. Soc. Am.115(6), 3033–3041.
Bregman AS (1990). Auditory scene analysis: The perceptual organization of sound. MIT Press, Cambridge, MA.
Nix J, Hohmann V (2007) Combined estimation of spectral envelopes and sound source direction of concurrent voices by multidimensional statistical filtering. IEEE Trans. Audio Speech and Lang. Proc. 15, 995–1008.
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Hohmann, V. (2008). Signal Processing in Hearing Aids. In: Havelock, D., Kuwano, S., Vorländer, M. (eds) Handbook of Signal Processing in Acoustics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30441-0_14
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