Emergent Mind

Directional MCLP Analysis and Reconstruction for Spatial Speech Communication

(2109.04544)
Published Sep 9, 2021 in eess.AS , cs.SD , and eess.SP

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 constituent signal components, separately at each node. The intersection between DoA directions at each node is used to compute the source position. Signal components computed at the node nearest to the estimated source position are taken as the signals for transmission. At the receiver, a four channel loud speaker (LS) setup is used for spatial reproduction, in which the source spatial image is reproduced relative to a chosen virtual listener position in the transmitter enclosure. Vector base amplitude panning (VBAP) method is used for direct component reproduction using the LS setup and the diffuse component is reproduced equally from all the loud speakers after decorrelation. This scheme of spatial speech communication is shown to be effective and more natural for hands-free telecommunication, through either loudspeaker listening or binaural headphone listening with head related transfer function (HRTF) based presentation.

We're not able to analyze this paper right now due to high demand.

Please check back later (sorry!).

Generate a summary of this paper on our Pro plan:

We ran into a problem analyzing this paper.

Newsletter

Get summaries of trending comp sci papers delivered straight to your inbox:

Unsubscribe anytime.