Prediction of hearing aid performance using the multiple model least squares technique

Author

Parsa, Vjay ; Jamieson, Donald G.

Author_Institution

Natural Centre for Audiology, Univ. of Western Ontario, London, Ont., Canada

Volume

1

fYear

2001

fDate

2001

Firstpage

515

Abstract

Measurement of noise and distortion in hearing aids is important for the design, fitting and assessment of these devices. In addition, it is imperative to test the hearing aids with speech signals to accurately predict their “real world” performance. In this paper, an adaptive system identification approach is taken to quantify the distortion and noise in a hearing aid. The hearing aid was modelled as a time varying autoregressive moving average (ARMA) system whose coefficients are estimated on a block-by-block basis using the multiple model least squares (MMLS) algorithm. Several speech-based distortion measures are derived from the modelling procedure which is shown to perform well in predicting perceptual judgements of hearing aid quality

Keywords

autoregressive moving average processes; hearing aids; identification; least squares approximations; time-varying systems; ARMA system; MMLS; adaptive system identification approach; assessment; block-by-block estimation; design; distortion; fitting; hearing aid performance; multiple model least squares technique; noise; perceptual judgement; speech signals; speech-based distortion measures; time varying autoregressive moving average system; Adaptive systems; Auditory system; Autoregressive processes; Distortion measurement; Hearing aids; Noise measurement; Predictive models; Speech; System identification; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2001. Canadian Conference on

Conference_Location

Toronto, Ont.

ISSN

0840-7789

Print_ISBN

0-7803-6715-4

Type

conf

DOI

10.1109/CCECE.2001.933737

Filename

933737