Time-frequency-masking-based Determined BSS with Application to Sparse IVA

Kohei Yatabe, Daichi Kitamura

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Most of the determined blind source separation (BSS) algorithms related to the independent component analysis (ICA) were derived from mathematical models of source signals. However, such derivation restricts the application of algorithms to explicitly definable source models, i.e., an implicit model associated with some signal-processing procedure cannot be utilized within such framework. In this paper, we propose an extension of the existing algorithm so that any time-frequency masking method (e.g., those developed in speech enhancement literature) can be incorporated into the determined BSS algorithm. As an application of the proposed algorithm, a sparse extension of the well-known independent vector analysis (IVA) is also proposed for illustrating the potentiality of the masking-based implicit source model.

本文言語English
ホスト出版物のタイトル2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ715-719
ページ数5
ISBN(電子版)9781479981311
DOI
出版ステータスPublished - 2019 5 1
イベント44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
継続期間: 2019 5 122019 5 17

出版物シリーズ

名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2019-May
ISSN(印刷版)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
CountryUnited Kingdom
CityBrighton
Period19/5/1219/5/17

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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