Real-Time Speech Extraction Based on Rank-Constrained Spatial Covariance Matrix Estimation and Spatially Regularized Independent Low-Rank Matrix Analysis With Fast Demixing Matrix Estimation

Real-Time Speech Extraction Based on Rank-Constrained Spatial Covariance Matrix Estimation and Spatially Regularized Independent Low-Rank Matrix Analysis With Fast Demixing Matrix Estimation

Real-time speech extraction is a valuable task and has diverse applications, such as speech recognition in a human-like avatar/robot and hearing aids. In this paper, we propose the real-time extension of a speech extraction method based on independent low-rank matrix analysis (ILRMA) and rank-constr...

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Bibliographic Details
Main Authors: Yuto Ishikawa, Tomohiko Nakamura, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, Kazunobu Kondo
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Independent low-rank matrix analysis
rank-constrained spatial covariance matrix estimation
real-time speech extraction
spatial regularization
Online Access:https://ieeexplore.ieee.org/document/11003054/
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