Navigation auf zora.uzh.ch

Search ZORA

ZORA (Zurich Open Repository and Archive)

Evaluating Multi-Channel Multi-Device Speech Separation Algorithms in the Wild: A Hardware-Software Solution

Ceolini, Enea; Kiselev, Ilya; Liu, Shih-Chii (2020). Evaluating Multi-Channel Multi-Device Speech Separation Algorithms in the Wild: A Hardware-Software Solution. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28:1428-1439.

Abstract

Evaluation methods for multi-channel speech separation algorithms in the real world are becoming increasingly important as the number of applications involving audio assistants and hearing aid devices continues to grow. To make such evaluations easier, this paper presents a multi-microphone hardware platform, WHISPER, built specifically for this purpose and its subsequent use for evaluating speech processing algorithms. The platform can also be constructed as an ad-hoc wireless acoustic sensor network (WASN) with high synchronization precision. Using WHISPER, we describe real-world experiments where an example speech separation algorithm is applied to mixtures of varying number of talkers and signal-to-noise ratios. The results when compared with those from a simulated environment, show the usefulness of WASNs and that simulations tend to underestimate the difficulty of speech separation in real-world scenarios. This work represents an important step towards developing a hardware-software framework for evaluating speech processing algorithms in the wild.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Physical Sciences > Computer Science (miscellaneous)
Physical Sciences > Acoustics and Ultrasonics
Physical Sciences > Computational Mathematics
Physical Sciences > Electrical and Electronic Engineering
Uncontrolled Keywords:Speech and Hearing, Media Technology, Linguistics and Language, Signal Processing, Acoustics and Ultrasonics, Instrumentation, Electrical and Electronic Engineering
Language:English
Date:1 January 2020
Deposited On:15 Jan 2021 09:11
Last Modified:24 Dec 2024 02:40
Publisher:Institute of Electrical and Electronics Engineers
ISSN:2329-9290
OA Status:Green
Publisher DOI:https://doi.org/10.1109/taslp.2020.2989545
Download PDF  'Evaluating Multi-Channel Multi-Device Speech Separation Algorithms in the Wild: A Hardware-Software Solution'.
Preview
  • Content: Accepted Version

Metadata Export

Statistics

Citations

Dimensions.ai Metrics
4 citations in Web of Science®
6 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

235 downloads since deposited on 15 Jan 2021
54 downloads since 12 months
Detailed statistics

Authors, Affiliations, Collaborations

Similar Publications