A summary of the REVERB challenge: State-of-the-art and remaining challenges in reverberant speech processing research

Kinoshita K, Delcroix M, Gannot S, Habets E, Haeb-Umbach R, Kellermann W, Leutnant V, Maas R, Nakatani T, Raj B, Sehr A, Yoshioka T (2016)

Publication Status: Published

Publication Type: Journal article, Original article

Publication year: 2016

Journal

EURASIP Journal on Advances in Signal Processing SpringerOpen

Book Volume: 2016

Pages Range: 1-19

Article Number: 7

Journal Issue: 1

DOI: 10.1186/s13634-016-0306-6

Abstract

In recent years, substantial progress has been made in the field of reverberant speech signal processing, including both single- and multichannel dereverberation techniques and automatic speech recognition (ASR) techniques that are robust to reverberation. In this paper, we describe the REVERB challenge, which is an evaluation campaign that was designed to evaluate such speech enhancement (SE) and ASR techniques to reveal the state-of-the-art techniques and obtain new insights regarding potential future research directions. Even though most existing benchmark tasks and challenges for distant speech processing focus on the noise robustness issue and sometimes only on a single-channel scenario, a particular novelty of the REVERB challenge is that it is carefully designed to test robustness against reverberation, based on both real, single-channel, and multichannel recordings. This challenge attracted 27 papers, which represent 25 systems specifically designed for SE purposes and 49 systems specifically designed for ASR purposes. This paper describes the problems dealt within the challenge, provides an overview of the submitted systems, and scrutinizes them to clarify what current processing strategies appear effective in reverberant speech processing.

Authors with CRIS profile

Emanuël Habets Professur für wahrnehmungsbasierte räumliche Audiosignalverarbeitung (AudioLabs) (Stiftungsprofessur) Walter Kellermann Professur für Signalverarbeitung Roland Maas Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS)

Involved external institutions

Bar-Ilan University IL Israel (IL) Universität Paderborn DE Germany (DE) Carnegie Mellon University US United States (USA) (US) Nippon Telegraph and Telephone (NTT) / 日本電信電話株式会社 JP Japan (JP) Ostbayerische Technische Hochschule Regensburg (OTH) DE Germany (DE)

How to cite

APA:

Kinoshita, K., Delcroix, M., Gannot, S., Habets, E., Haeb-Umbach, R., Kellermann, W.,... Yoshioka, T. (2016). A summary of the REVERB challenge: State-of-the-art and remaining challenges in reverberant speech processing research. EURASIP Journal on Advances in Signal Processing, 2016(1), 1-19. https://doi.org/10.1186/s13634-016-0306-6

MLA:

Kinoshita, Keisuke, et al. "A summary of the REVERB challenge: State-of-the-art and remaining challenges in reverberant speech processing research." EURASIP Journal on Advances in Signal Processing 2016.1 (2016): 1-19.

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