Sound field indicators (SFI) are proposed as a new feature set to estimate the hearing activity and reverberation time in hearing instruments. SFIs are based on physical measurements of the sound field. A variant thereof, called SFI short-time statistics SFIst^2, is obtained by computing mean and standard deviations of SFIs on 10 subframes. To show the utility of these meature sets for the mentioned prediction tasks, experiments are carried out on artificially reverberated recordings of a large variety of sounds encountered in daily life. In a classification scenario where the hearing activity is to be predicted, both SFI and SFIst^2 yield clearly superior accuracy even compared to hand-tailored features used in state-of-the-art hearing instruments. For regression on the reverberation time, the SFI-based features yield a lower residual error than standard feature sets and reach the performance of specially designed features. The hearing activity classification is mainly based on the average of the SFIs, while the standard deviation over sub-window is used heavily to predict the reverberation time.

Authors: Streich, Andreas P.; Feilner, Manuela; Stirnemann, Alfred; Buhmann, Joachim M.
Affiliations: ETH Zurich, Zurich, Switzerland; Phonak AG, Stäfa, Switzerland(See document for exact affiliation information.)
AES Convention: 128 (May 2010) Paper Number: 7985
Publication Date: May 1, 2010 Import into BibTeX
Subject: Spatial Signal Processing
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=15282

Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $33 for non-members and is free for AES members and E-Library subscribers.

Learn more about the AES E-Library

E-Library Location: (CD 128Papers)   /128/7985.pdf

Start a discussion about this paper!