Publication detail

Speaker activity driven neural speech extraction

DELCROIX, M. ŽMOLÍKOVÁ, K. OCHIAI, T. KINOSHITA, K. NAKATANI, T.

Original Title

Speaker activity driven neural speech extraction

Type

conference paper

Language

English

Original Abstract

Target speech extraction, which extracts the speech of a target speaker in a mixture given auxiliary speaker clues, has recently received increased interest. Various clues have been investigated such as pre-recorded enrollment utterances, direction information, or video of the target speaker. In this paper, we explore the use of speaker activity information as an auxiliary clue for single-channel neural network-based speech extraction. We propose a speaker activity driven speech extraction neural network (ADEnet) and show that it can achieve performance levels competitive with enrollmentbased approaches, without the need for pre-recordings. We further demonstrate the potential of the proposed approach for processing meeting-like recordings, where speaker activity obtained from a diarization system is used as a speaker clue for ADEnet. We show that this simple yet practical approach can successfully extract speakers after diarization, which leads to improved ASR performance when using a single microphone, especially in high overlapping conditions, with relative word error rate reduction of up to 25 %.

Keywords

Speech extraction, Speaker activity, Speech enhancement, Meeting recognition, Neural network

Authors

DELCROIX, M.; ŽMOLÍKOVÁ, K.; OCHIAI, T.; KINOSHITA, K.; NAKATANI, T.

Released

6. 6. 2021

Publisher

IEEE Signal Processing Society

Location

Toronto

ISBN

978-1-7281-7605-5

Book

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Pages from

6099

Pages to

6103

Pages count

5

URL

https://www.fit.vut.cz/research/publication/12479/

BibTex

@inproceedings{BUT171749,
  author="DELCROIX, M. and ŽMOLÍKOVÁ, K. and OCHIAI, T. and KINOSHITA, K. and NAKATANI, T.",
  title="Speaker activity driven neural speech extraction",
  booktitle="ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
  year="2021",
  pages="6099--6103",
  publisher="IEEE Signal Processing Society",
  address="Toronto",
  doi="10.1109/ICASSP39728.2021.9414998",
  isbn="978-1-7281-7605-5",
  url="https://www.fit.vut.cz/research/publication/12479/"
}