Completing Sets of Prototype Transfer Functions for Subspace-based Direction of Arrival Estimation of Multiple Speakers

2025-01-13

AI Summary

This paper addresses the challenge of multi-speaker direction-of-arrival (DOA) estimation for partially calibrated microphone arrays—such as binaural hearing aids augmented with an externally mounted microphone of unknown position—in noisy and reverberant environments. We propose a prototype transfer function (PTF) completion method grounded in subspace orthogonality. To our knowledge, this is the first approach enabling PTF set completion without prior knowledge of the external microphone’s geometry or additional calibration procedures, thereby relaxing the conventional requirement of full-array geometric calibration inherent to subspace-based DOA methods. By integrating subspace orthogonality analysis, MUSIC-based spectral search, and relative transfer function (RTF) vector matching, the method achieves significantly higher DOA estimation accuracy than baseline approaches using incomplete PTF sets in two-speaker scenarios. Moreover, it demonstrates robustness across arbitrary external microphone configurations.

Technology Category

• Machine Learning: Matrix & Tensor Methods
• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Activity and Plan Recognition

Application Category

• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

To estimate the direction of arrival (DOA) of multiple speakers, subspace-based prototype transfer function matching methods such as multiple signal classification (MUSIC) or relative transfer function (RTF) vector matching are commonly employed. In general, these methods require calibrated microphone arrays, which are characterized by a known array geometry or a set of known prototype transfer functions for several directions. In this paper, we consider a partially calibrated microphone array, composed of a calibrated binaural hearing aid and a (non-calibrated) external microphone at an unknown location with no available set of prototype transfer functions. We propose a procedure for completing sets of prototype transfer functions by exploiting the orthogonality of subspaces, allowing to apply matching-based DOA estimation methods with partially calibrated microphone arrays. For the MUSIC and RTF vector matching methods, experimental results for two speakers in noisy and reverberant environments clearly demonstrate that for all locations of the external microphone DOAs can be estimated more accurately with completed sets of prototype transfer functions than with incomplete sets. c{opyright}20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Problem

• Multi-speaker localization
• Noisy environments
• Partially-calibrated microphone arrays

Innovation

• Directional Transfer Function Completion
• Subspace Relationship
• Speaker Localization