Publication Details
Neural Target Speech Extraction: An overview
Delcroix Marc
OCHIAI, T.
Černocký Jan, prof. Dr. Ing. (DCGM)
Kinoshita Keisuke
Yu Dong
neural, speech, extraction
Humans can listen to a target speaker even in challenging acoustic conditions
that have noise, reverberation, and interfering speakers. This phenomenon is
known as the cocktail party effect . For decades, researchers have focused on
approaching the listening ability of humans. One critical issue is handling
interfering speakers because the target and nontarget speech signals share
similar characteristics, complicating their discrimination. Target speech/speaker
extraction (TSE) isolates the speech signal of a target speaker from a mixture of
several speakers, with or without noises and reverberations, using clues that
identify the speaker in the mixture. Such clues might be a spatial clue
indicating the direction of the target speaker, a video of the speaker's lips,
and a prerecorded enrollment utterance from which the speaker's voice
characteristics can be derived. TSE is an emerging field of research that has
received increased attention in recent years because it offers a practical
approach to the cocktail party problem and involves such aspects of signal
processing as audio, visual, and array processing as well as deep learning. This
article focuses on recent neural-based approaches and presents an in-depth
overview of TSE. We guide readers through the different major approaches,
emphasizing the similarities among frameworks and discussing potential future
directions.
@article{BUT185203,
author="ŽMOLÍKOVÁ, K. and DELCROIX, M. and OCHIAI, T. and ČERNOCKÝ, J. and KINOSHITA, K. and YU, D.",
title="Neural Target Speech Extraction: An overview",
journal="IEEE SIGNAL PROCESSING MAGAZINE",
year="2023",
volume="40",
number="3",
pages="8--29",
doi="10.1109/MSP.2023.3240008",
issn="1558-0792",
url="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10113382"
}