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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Veröffentlicht in:	IEEE access Jg. 13; S. 1
Hauptverfasser:	Ishikawa, Yuto, Nakamura, Tomohiko, Takamune, Norihiro, Kitamura, Daichi, Saruwatari, Hiroshi, Takahashi, Yu, Kondo, Kazunobu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Avatars Computing time Constraints Covariance matrices Covariance matrix Data mining Demixing Effectiveness Estimation Hearing aids Independent low-rank matrix analysis Matrix methods Noise Numerical stability Parameter estimation Performance evaluation rank-constrained spatial covariance matrix estimation Real time real-time speech extraction Real-time systems Regularization Robustness spatial regularization Speech Speech processing Speech recognition
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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