Coherence-Based Frequency Subset Selection For Binaural RTF-Vector-Based Direction of Arrival Estimation for Multiple Speakers

Abstract

Recently, a method has been proposed to estimate the direction of arrival (DOA) of a single speaker by minimizing the frequency-averaged Hermitian angle between an estimated relative transfer function (RTF) vector and a database of prototype anechoic RTF vectors. In this paper, we extend this method to multi-speaker localization by introducing the frequency-averaged Hermitian angle spectrum and selecting peaks of this spatial spectrum. To construct the Hermitian angle spectrum, we consider only a subset of frequencies, where it is likely that one speaker is dominant. We compare the effectiveness of the generalized magnitude squared coherence and two coherent-to-diffuse ratio (CDR) estimators as frequency selection criteria. Simulation results for estimating the DOAs of two speakers in a reverberant environment with diffuse-like babble noise using binaural hearing devices show that using the binaural effective-coherence-based CDR estimate as a frequency selection criterion yields the best performance.

This work has been submitted to the IEEE for possible publication

References in corpus (2)

• Coherent-to-Diffuse Power Ratio Estimation for Dereverberation
• Comparison of Binaural RTF-Vector-Based Direction of Arrival Estimation Methods Exploiting an External Microphone

Cited by in corpus (4)

• Assisted RTF-Vector-Based Binaural Direction of Arrival Estimation Exploiting a Calibrated External Microphone Array
• Comparison of Frequency-Fusion Mechanisms for Binaural Direction-of-Arrival Estimation for Multiple Speakers
• Exploiting an External Microphone for Binaural RTF-Vector-Based Direction of Arrival Estimation for Multiple Speakers
• Completing Sets of Prototype Transfer Functions for Subspace-based Direction of Arrival Estimation of Multiple Speakers