In this section
@inproceedings{Neo:2022:10.1109/IWAENC53105.2022.9914796,
author = {Neo, VW and Weiss, S and McKnight, S and Hogg, A and Naylor, PA},
doi = {10.1109/IWAENC53105.2022.9914796},
pages = {1--5},
publisher = {IEEE},
title = {Polynomial eigenvalue decomposition-based target speaker voice activity detection in the presence of competing talkers},
url = {http://dx.doi.org/10.1109/IWAENC53105.2022.9914796},
year = {2022}
}
TY - CPAPER
AB - Voice activity detection (VAD) algorithms are essential for many speech processing applications, such as speaker diarization, automatic speech recognition, speech enhancement, and speech coding. With a good VAD algorithm, non-speech segments can be excluded to improve the performance and computation of these applications. In this paper, we propose a polynomial eigenvalue decomposition-based target-speaker VAD algorithm to detect unseen target speakers in the presence of competing talkers. The proposed approach uses frame-based processing to compute the syndrome energy, used for testing the presence or absence of a target speaker. The proposed approach is consistently among the best in F1 and balanced accuracy scores over the investigated range of signal to interference ratio (SIR) from -10 dB to 20 dB.
AU - Neo,VW
AU - Weiss,S
AU - McKnight,S
AU - Hogg,A
AU - Naylor,PA
DO - 10.1109/IWAENC53105.2022.9914796
EP - 5
PB - IEEE
PY - 2022///
SP - 1
TI - Polynomial eigenvalue decomposition-based target speaker voice activity detection in the presence of competing talkers
UR - http://dx.doi.org/10.1109/IWAENC53105.2022.9914796
UR - https://ieeexplore.ieee.org/document/9914796
UR - http://hdl.handle.net/10044/1/98386
ER -
For more information about the group, please contact:
Dr Dan Goodman
+44 (0)20 7594 6264
d.goodman@imperial.ac.uk