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'Silencing the Echoes' - Processing of Reverberant Speech

The Reverberant Voice Enhancement and Recognition Benchmark challenge has recently been organized, in order to enable researchers in the field of reverberant speech processing to carry out comprehensive evaluations of their methods based on a common database and common evaluation metrics. Inspired by the great interest generated by this challenge, we invite contributions on processing of reverberant speech signals for both signal enhancement to increase perceptual speech quality and for robust recognition of reverberant speech.

Edited by: Sharon Gannot, Armin Sehr, Emanuël Habets, Keisuke Kinoshita, Walter Kellermann and Reinhold Haeb-Umbach

  1. Research

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

    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 (AS...

    Keisuke Kinoshita, Marc Delcroix, Sharon Gannot, Emanuël A. P. Habets, Reinhold Haeb-Umbach, Walter Kellermann, Volker Leutnant, Roland Maas, Tomohiro Nakatani, Bhiksha Raj, Armin Sehr and Takuya Yoshioka

    EURASIP Journal on Advances in Signal Processing 2016 2016:7

    Published on: 18 January 2016

  2. Research

    Speech dereverberation for enhancement and recognition using dynamic features constrained deep neural networks and feature adaptation

    This paper investigates deep neural networks (DNN) based on nonlinear feature mapping and statistical linear feature adaptation approaches for reducing reverberation in speech signals. In the nonlinear feature...

    Xiong Xiao, Shengkui Zhao, Duc Hoang Ha Nguyen, Xionghu Zhong, Douglas L. Jones, Eng Siong Chng and Haizhou Li

    EURASIP Journal on Advances in Signal Processing 2016 2016:4

    Published on: 13 January 2016

  3. Research

    Feature enhancement of reverberant speech by distribution matching and non-negative matrix factorization

    This paper describes a novel two-stage dereverberation feature enhancement method for noise-robust automatic speech recognition. In the first stage, an estimate of the dereverberated speech is generated by mat...

    Sami Keronen, Heikki Kallasjoki, Kalle J. Palomäki, Guy J. Brown and Jort F. Gemmeke

    EURASIP Journal on Advances in Signal Processing 2015 2015:76

    Published on: 20 August 2015

  4. Research

    Front-end technologies for robust ASR in reverberant environments—spectral enhancement-based dereverberation and auditory modulation filterbank features

    This paper presents extended techniques aiming at the improvement of automatic speech recognition (ASR) in single-channel scenarios in the context of the REVERB (REverberant Voice Enhancement and Recognition B...

    Feifei Xiong, Bernd T. Meyer, Niko Moritz, Robert Rehr, Jörn Anemüller, Timo Gerkmann, Simon Doclo and Stefan Goetze

    EURASIP Journal on Advances in Signal Processing 2015 2015:70

    Published on: 5 August 2015

  5. Research

    Combination of MVDR beamforming and single-channel spectral processing for enhancing noisy and reverberant speech

    This paper presents a system aiming at joint dereverberation and noise reduction by applying a combination of a beamformer with a single-channel spectral enhancement scheme. First, a minimum variance distortio...

    Benjamin Cauchi, Ina Kodrasi, Robert Rehr, Stephan Gerlach, Ante Jukić, Timo Gerkmann, Simon Doclo and Stefan Goetze

    EURASIP Journal on Advances in Signal Processing 2015 2015:61

    Published on: 23 July 2015

  6. Research

    Strategies for distant speech recognitionin reverberant environments

    Reverberation and noise are known to severely affect the automatic speech recognition (ASR) performance of speech recorded by distant microphones. Therefore, we must deal with reverberation if we are to realiz...

    Marc Delcroix, Takuya Yoshioka, Atsunori Ogawa, Yotaro Kubo, Masakiyo Fujimoto, Nobutaka Ito, Keisuke Kinoshita, Miquel Espi, Shoko Araki, Takaaki Hori and Tomohiro Nakatani

    EURASIP Journal on Advances in Signal Processing 2015 2015:60

    Published on: 19 July 2015

  7. Research

    Reverberant speech recognition exploiting clarity index estimation

    We present single-channel approaches to robust automatic speech recognition (ASR) in reverberant environments based on non-intrusive estimation of the clarity index (C 50). Our best perfor...

    Pablo Peso Parada, Dushyant Sharma, Patrick A. Naylor and Toon van Waterschoot

    EURASIP Journal on Advances in Signal Processing 2015 2015:54

    Published on: 1 July 2015

  8. Research

    Effectiveness of dereverberation, feature transformation, discriminative training methods, and system combination approach for various reverberant environments

    The recently released REverberant Voice Enhancement and Recognition Benchmark (REVERB) challenge includes a reverberant automatic speech recognition (ASR) task. This paper describes our proposed system based o...

    Yuuki Tachioka, Tomohiro Narita and Shinji Watanabe

    EURASIP Journal on Advances in Signal Processing 2015 2015:52

    Published on: 30 June 2015

  9. Research

    Speech recognition in reverberant and noisy environments employing multiple feature extractors and i-vector speaker adaptation

    The REVERB challenge provides a common framework for the evaluation of feature extraction techniques in the presence of both reverberation and additive background noise. State-of-the-art speech recognition sys...

    Md Jahangir Alam, Vishwa Gupta, Patrick Kenny and Pierre Dumouchel

    EURASIP Journal on Advances in Signal Processing 2015 2015:50

    Published on: 19 June 2015

  10. Research

    Microphone array power ratio for quality assessment of reverberated speech

    Speech signals in enclosed environments are often distorted by reverberation and noise. In speech communication systems with several randomly distributed microphones, involving a dynamic speaker and unknown so...

    Reuven Berkun and Israel Cohen

    EURASIP Journal on Advances in Signal Processing 2015 2015:49

    Published on: 18 June 2015