Successive Speaker Relative Transfer Function Estimation Through Relative Transfer Matrix in Noisy Reverberant Environments

Estimating the Relative Transfer Functions (ReTFs) of multiple speakers in a noisy reverberant environment are beneficial to signal processing applications of acoustic scene analysis, denoising, dereverberation, signal enhancement, and separation. Whilst most audio applications exploit the covariance matrix structure of multichannel recordings, estimating ReTF in the presence of simultaneously active multiple speakers is still considered to be a challenging problem. In this paper, we propose a novel method for estimating the ReTF using the relative transfer matrix (ReTM) of multiple microphones for multi-talker scenarios, which is suitable for noisy reverberant rooms. The method is based on the noise-only ReTM, and calculates the covariance matrices of (i) the first speaker and noise, and (ii) both speakers and noise at two microphone groups to reconstruct the ReTF of the second speaker. We demonstrate the ReTF estimation accuracy using numerical simulation of two speakers and two noise sources in a reverberant environment. The proposed method offers an accurate estimation with a low Hermitian angle. Additionally, the proposed algorithm is shown to better extract the voice of the successive speaker from the noisy microphone recordings over various SNR levels using a minimum variance distortionless response beamformer with improved noise reduction performance.