This engineering brief outlines how Machine Learning (ML) can be used to estimate objective sound source distance by examining both the temporal and spectral content of binaural signals. A simple ML algorithm is presented that is capable of predicting source distance to within half a meter in a previously unseen environment. This algorithm is trained using a selection of features extracted from synthesized binaural speech. This enables us to determine which of a selection of cues can be best used to predict sound source distance in binaural audio. The research presented can be seen not only as an exercise in ML but also as a means of investigating how binaural hearing works.

Authors: O'Dwyer, Hugh; Csadi, Sebastian; Bates, Enda; Boland, Francis M.
Affiliation: Trinity College, Dublin, Ireland
AES Convention: 146 (March 2019) eBrief:509
Publication Date: March 10, 2019
Subject: E-Brief Poster Session 2

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