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Speech Dereverberation Based on Variance-Normalized Delayed Linear Prediction
TLDR
NDLP can robustly estimate an inverse system for late reverberation in the presence of noise without greatly distorting a direct speech signal and can be implemented in a computationally efficient manner in the time-frequency domain.
The reverb challenge: A common evaluation framework for dereverberation and recognition of reverberant speech
TLDR
A common evaluation framework including datasets, tasks, and evaluation metrics for both speech enhancement and ASR techniques is proposed, which will be used as a common basis for the REVERB (REverberant Voice Enhancement and Recognition Benchmark) challenge.
Generalization of Multi-Channel Linear Prediction Methods for Blind MIMO Impulse Response Shortening
TLDR
This paper generalizes existing dereverberation methods using subband-domain multi-channel linear prediction filters so that the resultant generalized algorithm can blindly shorten a multiple-input multiple-output room impulse response between a set of unknown number of sources and a microphone array.
The NTT CHiME-3 system: Advances in speech enhancement and recognition for mobile multi-microphone devices
TLDR
NTT's CHiME-3 system is described, which integrates advanced speech enhancement and recognition techniques, which achieves a 3.45% development error rate and a 5.83% evaluation error rate.
Suppression of Late Reverberation Effect on Speech Signal Using Long-Term Multiple-step Linear Prediction
TLDR
A room impulse response is assumed to consist of three parts: a direct-path response, early reflections and late reverberations, which is known to be a major cause of ASR performance degradation.
A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research
TLDR
The REVERB challenge is described, which is an evaluation campaign that was designed to evaluate such speech enhancement and ASR techniques to reveal the state-of-the-art techniques and obtain new insights regarding potential future research directions.
Neural Network-Based Spectrum Estimation for Online WPE Dereverberation
TLDR
A novel speech dereverberation framework that utilizes deep neural network (DNN)-based spectrum estimation to construct linear inverse filters is proposed that outperforms the conventional WPE, and improves the ASR performance in real noisy reverberant environments in both single-channel and multichannel cases.
Making Machines Understand Us in Reverberant Rooms: Robustness Against Reverberation for Automatic Speech Recognition
TLDR
For a number of unexplored but important applications, distant microphones are a prerequisite for extending the availability of speech recognizers as well as enhancing the convenience of existing speech recognition applications.
Robust MVDR beamforming using time-frequency masks for online/offline ASR in noise
TLDR
Experimental results show that the CGMM-based approach outperforms a recently proposed mask estimator based on a Watson mixture model and is extended to an online speech enhancement scenario, which allows this technique to be used in an online recognition setup.
Blind speech dereverberation with multi-channel linear prediction based on short time fourier transform representation
TLDR
Methods for implementing MCLP based speech dereverberation that allow it to work in the short time Fourier transform (STFT) domain with much less computing cost are presented.
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