@article{KinoshitaDelcroixGannotetal., author = {Kinoshita, Keisuke and Delcroix, Marc and Gannot, Sharon and Habets, Emanuel A. P. and Haeb-Umbach, Reinhold and Kellermann, Walter and Leutnant, Volker and Maas, Roland and Nakatani, Tomohiro and Raj, Bhiksha and Sehr, Armin and Yoshioka, Takuya}, title = {A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research}, series = {Eurasip journal on advances in signal processing}, volume = {2016}, journal = {Eurasip journal on advances in signal processing}, publisher = {Springer Nature}, 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.}, language = {en} } @inproceedings{YoshiokaSehrDelcroixetal., author = {Yoshioka, Takuya and Sehr, Armin and Delcroix, Marc and Kinoshita, Keisuke and Maas, Roland and Nakatani, Tomohiro and Kellermann, Walter}, title = {Survey on approaches to speech recognition in reverberant environments}, series = {Asia-Pacific Signal \& Information Processing Association annual summit and conference (APSIPA ASC), 2012 : Hollywood, California, USA, 3 - 6 Dec. 2012}, booktitle = {Asia-Pacific Signal \& Information Processing Association annual summit and conference (APSIPA ASC), 2012 : Hollywood, California, USA, 3 - 6 Dec. 2012}, publisher = {IEEE}, isbn = {978-0-6157-0050-2}, abstract = {This paper overviews the state of the art in reverberant speech processing from the speech recognition viewpoint. First, it points out that the key to successful reverberant speech recognition is to account for long-term dependencies between reverberant observations obtained from consecutive time frames. Then, a diversity of approaches that exploit the long-term dependencies in various ways is described, ranging from signal and feature dereverberation to acoustic model compensation tailored to reverberation. A framework for classifying those approaches is presented to highlight similarities and differences between them.}, language = {en} }