NDLI: Estimation of relative transfer function in the presence of stationary noise based on segmental power spectral density matrix subtraction

Content Provider	IEEE Xplore Digital Library
Author	Xiaofei Li Girin, L. Horaud, R. Gannot, S.
Copyright Year	2015
Description	Author affiliation: INRIA Grenoble Rhone-Alpes, Grenoble, France (Xiaofei Li; Girin, L.; Horaud, R.) \|\| Fac. of Eng., Bar-Ilan Univ., Ramat-Gan, Israel (Gannot, S.)
Abstract	This paper addresses the problem of relative transfer function (RTF) estimation in the presence of stationary noise. We propose an RTF identification method based on segmental power spectral density (PSD) matrix subtraction. First multiple channel microphone signals are divided into segments corresponding to speech-plus-noise activity and noise-only. Then, the subtraction of two segmental PSD matrices leads to an almost noise-free PSD matrix by reducing the stationary noise component and preserving non-stationary speech component. This noise-free PSD matrix is used for single speaker RTF identification by eigenvalue decomposition. Experiments are performed in the context of sound source localization to evaluate the efficiency of the proposed method.
Starting Page	320
Ending Page	324
File Size	986089
Page Count	5
File Format	PDF
ISBN	9781467369978
DOI	10.1109/ICASSP.2015.7177983
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-19
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise Speech Estimation Microphones Cameras Transfer functions Acoustics stationary noise microphone array relative transfer function
Content Type	Text
Resource Type	Article

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