Sequential Estimation of Relative Transfer Function in Application of Acoustic Beamforming

Jounghoon Beh

doi:10.3390/info11110505

Abstract

In this paper, a sequential approach is proposed to estimate the relative transfer functions (RTF) used in developing a generalized sidelobe canceller (GSC). The latency in calibrating microphone arrays for GSC, often suffered by conventional approaches involving batch operations, is significantly reduced in the proposed sequential method. This is accomplished by an immediate generation of the RTF from initial input segments and subsequent updates of the RTF as the input stream continues. From the experimental results via the mean square error (MSE) criterion, it has been shown that the proposed method exhibits improved performance over the conventional batch approach as well as over recently introduced least mean squares approaches.

Highlights

Acoustic beamforming using a microphone array has been considered as one of the most effective front-end tools for enhancing acoustic signal quality in speech communication and automatic speech recognition
From the experimental results via the mean square error (MSE) criterion, it has been shown that the proposed method exhibits improved performance over the conventional batch approach as well as over recently introduced least mean squares approaches
In the recently proposed acoustic beamforming techniques based on the generalized sidelobe canceller (GSC) such as [1,2,3], it has been clearly shown that precise estimation of relative transfer functions (RTFs) between each microphone of an array is critical for the effective performance of a beamformer

Summary

Introduction

Acoustic beamforming using a microphone array has been considered as one of the most effective front-end tools for enhancing acoustic signal quality in speech communication and automatic speech recognition. In the recently proposed acoustic beamforming techniques based on the generalized sidelobe canceller (GSC) such as [1,2,3], it has been clearly shown that precise estimation of relative transfer functions (RTFs) between each microphone of an array is critical for the effective performance of a beamformer. The estimated RTF plays a key role in calibrating the microphone array for compensating the signal leakage problem [1] in GSC, and it is used for constructing the matched beamformers [2] in scenarios where the desired signal is contaminated by directional non-stationary interference, such as a competing speaker. The aim of this paper is to develop an effective method to estimate the RTFs for acoustic beamforming. Existing least square-based methods, such as the batch least squares (BLS) approach, require a set of input data blocks for initial calibration [1,2]. An adaptive form of RTF estimation using the least mean squares (LMS)

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Conclusion