本文将单说话人 RTF 厄米角 DOA 估计扩展为多说话人空间谱峰值定位，并证明基于双耳有效相干性的 CDR 频率子集选择性能最佳。
摘要：
最近，已有研究提出一种方法，通过最小化估计的相对传递函数（RTF）向量与原型无混响 RTF 向量数据库之间的频率平均厄米角，来估计单个说话人的波达方向（DOA）。本文将该方法扩展到多说话人定位，引入频率平均厄米角谱并选择该空间谱的峰值。为构建厄米角谱，我们仅考虑一个频率子集，在这些频率上很可能由一名说话人占主导。我们比较了广义幅度平方相干性与两种相干-扩散比（CDR）估计器作为频率选择准则的有效性。在使用双耳助听设备、混响环境且存在类扩散多人嘈杂噪声的条件下，对两名说话人进行 DOA 估计的仿真结果表明，采用基于双耳有效相干性的 CDR 估计作为频率选择准则可获得最佳性能。
英文摘要：
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.
Besides suppressing all undesired sound sources, an important objective of a binaural noise reduction algorithm for hearing devices is the preservation of the binaural cues, aiming at preserving the spatial perception of the acoustic scene. A well-known binaural noise reduction algorithm is the binaural minimum variance distortionless response beamformer, which can be steered using the relative transfer function (RTF) vector of the desired source, relating the acoustic transfer functions between the desired source and all microphones to a reference microphone. In this paper, we propose a compu…
The binaural minimum-variance distortionless-response (BMVDR) beamformer is a well-known noise reduction algorithm that can be steered using the relative transfer function (RTF) vector of the desired speech source. Exploiting the availability of an external microphone that is spatially separated from the head-mounted microphones, an efficient method has been recently proposed to estimate the RTF vector in a diffuse noise field. When multiple external microphones are available, different RTF vector estimates can be obtained by using this method for each external microphone. In this paper, we pr…
Assisted RTF-Vector-Based Binaural Direction of Arrival Estimation Exploiting a Calibrated External Microphone Array
University of Oldenburg, Department of Medical Physics and Acoustics（奥尔登堡大学医学物理与声学系）；Cluster of Excellence Hearing4all, Oldenburg, Germany（卓越中心Hearing4all）
Peking University（北京大学）；Westlake University（西湖大学）；Westlake Institute for Advanced Study（西湖高等研究院）
Direct-path relative transfer function (DP-RTF) refers to the ratio between the direct-path acoustic transfer functions of two microphone channels. Though DP-RTF fully encodes the sound spatial cues and serves as a reliable localization feature, it is often erroneously estimated in the presence of noise and reverberation. This paper proposes to learn DP-RTF with deep neural networks for robust binaural sound source localization. A DP-RTF learning network is designed to regress the binaural sensor signals to a real-valued representation of DP-RTF. It consists of a branched convolutional neural …
In this paper we consider a binaural hearing aid setup, where in addition to the head-mounted microphones an external microphone is available. For this setup, we investigate the performance of several relative transfer function (RTF) vector estimation methods to estimate the direction of arrival (DOA) of the target speaker in a noisy and reverberant acoustic environment. More in particular, we consider the state-of-the-art covariance whitening (CW) and covariance subtraction (CS) methods, either incorporating the external microphone or not, and the recently proposed spatial coherence (SC) meth…
Sound source proximity and distance estimation are of great interest in many practical applications, since they provide significant information for acoustic scene analysis. As both tasks share complementary qualities, ensuring efficient interaction between these two is crucial for a complete picture of an aural environment. In this paper, we aim to investigate several ways of performing joint proximity and direction estimation from binaural recordings, both defined as coarse classification problems based on Deep Neural Networks (DNNs). Considering the limitations of binaural audio, we propose …
Multi-Speaker DOA Estimation in Binaural Hearing Aids using Deep Learning and Speaker Count Fusion
School of Electrical Engineering and Computer Science, University of Ottawa, Canada（Ottawa大学电气与计算机科学学院, 加拿大）；Department of Electrical and Computer Engineering, Universite de Sherbrooke, Canada（Sherbrooke大学电气与计算机工程系, 加拿大）；WS Audiology, Germany（德国WS听觉学）
In this paper, a binaural beamforming algorithm for hearing aid applications is introduced.The beamforming algorithm is designed to be robust to some error in the estimate of the target speaker direction. The algorithm has two main components: a robust target linearly constrained minimum variance (TLCMV) algorithm based on imposing two constraints around the estimated direction of the target signal, and a post-processor to help with the preservation of binaural cues. The robust TLCMV provides a good level of noise reduction and low level of target distortion under realistic conditions. The pos…
End-to-end multi-channel speaker extraction and binaural speech synthesis
Laboratory of Noise and Audio Research, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China（声学研究所噪声与音频研究实验室，中国科学院，北京，中国）；University of Chinese Academy of Sciences, Beijing, China（中国科学院大学，北京，中国）；Communication University of China, Beijing, China（中国传媒大学，北京，中国）；Tianjin 712 Communication & Broadcasting Co., Ltd.（天津712通信广播有限公司）；Tianjin Tianan Borui Technology Co., Ltd.（天津天安伯瑞科技有限公司）
The proposed Circular statistics-based Inter-Microphone Phase difference estimation Localizer (CIMPL) method is tailored toward binaural hearing aid systems with microphone arrays in each unit. The method utilizes the circular statistics (circular mean and circular variance) of inter-microphone phase difference (IPD) across different microphone pairs. These IPDs are firstly mapped to time delays through a variance-weighted linear fit, then mapped to azimuth direction-of-arrival (DoA) and lastly information of different microphone pairs is combined. The variance is carried through the different…
