Beamforming with Interaural Time-To-Level Difference Conversion for Hearing Loss Compensation

This collection of MATLAB code relates to work by De Vries et al. [1]. In this paper, a novel beamformer (bfBcc.m) is proposed that performs a low-frequency conversion from interaural time to level differences [2] on all sources, next to noise/interference reduction. Its performance is evaluated and compared to pre-existing binaural beamformers.

A demo script is included as an example demonstration of how the included functions can be used. This demo script also generates the MATLAB figures that appear in the paper. Brief function descriptions are provided for all functions, which can also be called up through the help command.

The functionsExt folder contains necessary external functions originating from ANSI/ASA [3], Beutelmann et al. [4] and Andersen et al. [5]. The data folder contains speech samples from the TIMIT Acoustic-Phonetic Continuous Speech Corpus [6] and head related transfer functions (HRTFs) from the Oldenburg database of HRTFs [7].

[1] J. W. de Vries, T.-J. Bäumer, S. Töpken, R. Heusdens, S. van de Par, and R. C. Hendriks, “Beamforming with Interaural Time-To-Level Difference Conversion for Hearing Loss Compensation,” in Proc. 2025 IEEE Workshop Appl. Signal Process. Audio Acoust., Tahoe City, CA, USA, submitted for publication.
[2] T.-J. Bäumer, S. Töpken, R. C. Hendriks, P. Goli, and S. van de Par, “A binaural cue transformation method to preserve spatial release from masking in listeners with impaired ITD processing,” in Proc. DAS|DAGA 2025, Copenhagen, Denmark, pp. 1116–1119.
[3] Methods for Calculation of the Speech Intelligibility Index, ANSI/ASA Standard S3.5-1997.
[4] R. Beutelmann, T. Brand, and B. Kollmeier, “Revision, extension, and evaluation of a binaural speech intelligibility model,” J. Acoust. Soc. Amer., vol. 127, no. 4, pp. 2479–2497, Apr. 2010.
[5] A. H. Andersen, J. M. de Haan, Z.-H. Tan, and J. Jensen, “Refinement and validation of the binaural short time objective intelligibility measure for spatially diverse conditions,” Speech Commun., vol. 102, pp. 1–13, Sep. 2018.
[6] J. S. Garofolo et al., 1993, “TIMIT acoustic-phonetic continuous speech corpus,” Linguistic Data Consortium, doi: https://doi.org/10.35111/17gk-bn40.
[7] F. Denk, S. M. A. Ernst, S. D. Ewert, and B. Kollmeier, “Adapting hearing devices to the individual ear acoustics: Database and target response correction functions for various device styles,” Trends Hearing, vol. 22, pp. 1–19, 2018.