Publication detail
Investigation of Speaker Representation for Target-Speaker Speech Processing
ASHIHARA, T. MORIYA, T. HORIGUCHI, S. PENG, J. OCHIAI, T. DELCROIX, M. MATSUURA, K. SATO, H.
Original Title
Investigation of Speaker Representation for Target-Speaker Speech Processing
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
Target-speaker speech processing (TS) tasks, such as target-speaker automatic speech recognition (TS-ASR), target speech extraction (TSE), and personal voice activity detection (p-VAD), are important for extracting information about a desired speaker's speech even when it is corrupted by interfering speakers. While most studies have focused on training schemes or system architectures for each specific task, the auxiliary network for embedding target-speaker cues has not been investigated comprehensively in a unified cross- task evaluation. Therefore, this paper aims to address a fundamental question: what is the preferred speaker embedding for TS tasks? To this end, for the TS-ASR, TSE, and p-VAD tasks, we compare pre-trained speaker encoders (i.e., self-supervised or speaker recog- nition models) that compute speaker embeddings from pre-recorded enrollment speech of the target speaker with ideal speaker embed- dings derived directly from the target speaker's identity in the form of a one-hot vector. To further understand the properties of ideal speaker embedding, we optimize it using a gradient-based approach to improve performance on the TS task. Our analysis reveals that speaker verification performance is somewhat unrelated to TS task performances, the one-hot vector outperforms enrollment-based ones, and the optimal embedding depends on the input mixture.
Keywords
peaker representation, target-speaker automatic speech recognition, target speech extraction, personal voice activity detection, self-supervised learning
Authors
ASHIHARA, T.; MORIYA, T.; HORIGUCHI, S.; PENG, J.; OCHIAI, T.; DELCROIX, M.; MATSUURA, K.; SATO, H.
Publisher
IEEE Signal Processing Society
Location
Macao
ISBN
979-8-3503-9225-8
Book
Proc. 2024 IEEE Spoken Language Technology Workshop (SLT)
Pages from
423
Pages to
430
Pages count
8
URL
BibTex
@inproceedings{BUT196770,
author="ASHIHARA, T. and MORIYA, T. and HORIGUCHI, S. and PENG, J. and OCHIAI, T. and DELCROIX, M. and MATSUURA, K. and SATO, H.",
title="Investigation of Speaker Representation for Target-Speaker Speech Processing",
booktitle="Proc. 2024 IEEE Spoken Language Technology Workshop (SLT)",
pages="423--430",
publisher="IEEE Signal Processing Society",
address="Macao",
doi="10.1109/SLT61566.2024.10832160",
isbn="979-8-3503-9225-8",
url="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10832160"
}
Documents