Directional MCLP Analysis and Reconstruction for Spatial Speech Communication
Srikanth Raj Chetupalli, and Thippur V. Sreenivas

TL;DR
This paper presents a novel method for spatial speech communication that estimates source position and signal components using distributed microphone arrays and reconstructs the speech spatially for natural hands-free telecommunication.
Contribution
It introduces a joint estimation approach for source DoA and signal components using multi-channel linear prediction and a diffuse component model, enabling effective spatial reconstruction.
Findings
Effective source localization using DoA intersection
Natural spatial reproduction with VBAP and diffuse decorrelation
Improved hands-free telecommunication experience
Abstract
Spatial speech communication, i.e., the reconstruction of spoken signal along with the relative speaker position in the enclosure (reverberation information) is considered in this paper. Directional, diffuse components and the source position information are estimated at the transmitter, and perceptually effective reproduction is considered at the receiver. We consider spatially distributed microphone arrays for signal acquisition, and node specific signal estimation, along with its direction of arrival (DoA) estimation. Short-time Fourier transform (STFT) domain multi-channel linear prediction (MCLP) approach is used to model the diffuse component and relative acoustic transfer function is used to model the direct signal component. Distortion-less array response constraint and the time-varying complex Gaussian source model are used in the joint estimation of source DoA and the…
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Taxonomy
TopicsSpeech and Audio Processing · Advanced Adaptive Filtering Techniques · Hearing Loss and Rehabilitation
