Speech Dereverberation
17 papers with code • 4 benchmarks • 5 datasets
Removing reverberation from audio signals
Benchmarks
These leaderboards are used to track progress in Speech Dereverberation
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WHAM!
Latest papers
Receptive Field Analysis of Temporal Convolutional Networks for Monaural Speech Dereverberation
A feature of TCNs is that they have a receptive field (RF) dependent on the specific model configuration which determines the number of input frames that can be observed to produce an individual output frame.
Task-specific Optimization of Virtual Channel Linear Prediction-based Speech Dereverberation Front-End for Far-Field Speaker Verification
Developing a single-microphone speech denoising or dereverberation front-end for robust automatic speaker verification (ASV) in noisy far-field speaking scenarios is challenging.
Late reverberation suppression using U-nets
DiegoLeon96/Neural-Speech-Dereverberation
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In real-world settings, speech signals are almost always affected by reverberation produced by the working environment; these corrupted signals need to be \emph{dereverberated} prior to performing, e. g., speech recognition, speech-to-text conversion, compression, or general audio enhancement.
Blind Room Parameter Estimation Using Multiple-Multichannel Speech Recordings
Knowing the geometrical and acoustical parameters of a room may benefit applications such as audio augmented reality, speech dereverberation or audio forensics.
HiFi-GAN: High-Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks
rishikksh20/hifigan-denoiser
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Real-world audio recordings are often degraded by factors such as noise, reverberation, and equalization distortion.
Real-time Single-channel Dereverberation and Separation with Time-domainAudio Separation Network
mpariente/asteroid
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ISCA Interspeech 2018
We investigate the recently proposed Time-domain Audio Sep-aration Network (TasNet) in the task of real-time single-channel speech dereverberation.
Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition
wangkenpu/rsrgan
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First, we study the effectiveness of different dereverberation networks (the generator in GAN) and find that LSTM leads a significant improvement as compared with feed-forward DNN and CNN in our dataset.
