A binaural localization model that resolves front-back confusions through head movements.

Abstract

It is well known that head movements are instrumental in resolving front/back confusions in human sound localization. A mechanism for a binaural model is proposed here to extent current cross-correlation models to compensate for head movements. The algorithm tracks sound sources in the head-related coordinate system (HRCS) as well as in the room-related coordinate system (RRCS). It is also aware of the current head position within the room. The sounds are positioned in space using an HRTF catalog at 1 deg azimuthal resolution. The position of the sound source is determined through the inter-aural cross-correlation (IACC) functions across several auditory bands, which are mapped to functions of azimuth and superposed. The maxima of the cross-correlation functions determine the position of the sound source, but unfortunately, usually two peaks occur—one at or near the correct location and the second one at the front/back reversed position. When the model is programed to virtually turn its head, the degree-based cross-correlation functions are shifted with current head angle to match the RRCS. During this procedure, the IACC peak for the correct hemisphere will prevail if integrated over time for the duration of the head movement, whereas the front/back reversed peak will average out.

Front–back localization in simulated rectangular rooms

“…Although Inter-Aural Cross-Correlation (IACC) has been developed mainly for estimating the spaciousness in concert halls [20,1,33,7]. Braasch et al [6] proposed an algorithm that identifies sound sources by analyzing the IACC in the head-related coordinate system and room-related coordinate system. An algorithm for localizing the position of sound sources by combining ITD with spectral information has been proposed by Ovcharenko et al [21].…”

“…The ability of people to recognize if sound is coming from the front or from the back, is to a great extent based on sound source location dependent acoustic filtering effects of the pinna. This allows a listener to interpret spectral and level features of the perceived sound at high frequencies (3)(4)(5)(6)(7) to localize the source [2,13,14,19,17]. Monaural cues are strongly dependent on the shape of the pinna and are highly individual.…”