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Author Somani, Dipen ♦ Patel, Vinal ♦ George, Nithin V. ♦ Pradhan, Somanath
Source IIT Gandhinagar
Content type Text
Publisher IEEE
Language English
Subject Keyword Loudspeakers ♦ Speech ♦ Acoustics ♦ Delays ♦ Convergence ♦ Microphones
Abstract Acoustic feedback cancellation is one of the challenging tasks in the design of a behind the ear (BTE) digital hearing aid. This feedback cancellation is usually achieved using an adaptive filter. The finite correlation between the desired microphone input signal and the input signal to the loudspeaker results in a biased estimation of the adaptive filter, which may produce disturbances in the hearing aid. Prediction error method (PEM) has been used in literature to reduce the bias effects. The convergence of a PEM based feedback canceller can be improved by implementing the adaptive filter in the subband domain. However, a direct subband implementation results in aliasing issues, band-edge problems and introduces a delay due to analysis and synthesis filters. In order to reduce the aliasing and delay issues, a delayless subband implementation of a PEM based feedback canceller is designed in this paper. A delayless multiband-structured subband implementation of the feedback canceller is also attempted to further reduce the aliasing and band-edge effects. This implementation aims at having all the subbands collectively updating the fullband adaptive filter, without the need for a subband to fullband weight conversion and offers improved feedback cancellation at reduced computational load in comparison with a delayless subband implementation of a PEM based feedback canceller. In addition, an attempt has been made to further improve the convergence behaviour by using an improved proportionate learning scheme. The improved convergence offered by the proposed scheme is evident from the simulation study. The improvement has been further quantified using a perceptual evaluation of speech quality and the proposed approach has been shown to provide enhanced speech quality.
ISSN 23299290
Learning Resource Type Article
Publisher Date 2017-08-01
e-ISSN 23299304
Journal IEEE/ACM Transactions on Audio, Speech and Language Processing
Volume Number 25
Issue Number 8
Starting Page 1633
Ending Page 1643