Speech Dereverberation
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Benchmarks
Most implemented
AV-RIR: Audio-Visual Room Impulse Response Estimation
StoRM: A Diffusion-based Stochastic Regeneration Model for Speech Enhancement and Dereverberation
Deformable Temporal Convolutional Networks for Monaural Noisy Reverberant Speech Separation
MESH2IR: Neural Acoustic Impulse Response Generator for Complex 3D Scenes
Papers
LipsAM: Lipschitz-Continuous Amplitude Modifier for Audio Signal Processing and its Application to Plug-and-Play Dereverberation
The robustness of deep neural networks (DNNs) can be certified through their Lipschitz continuity, which has made the construction of Lipschitz-continuous DNNs an active research field. However, DNNs for audio processing…
Speech DereverberationIs Phase Really Needed for Weakly-Supervised Dereverberation ?
In unsupervised or weakly-supervised approaches for speech dereverberation, the target clean (dry) signals are considered to be unknown during training. In that context, evaluating to what extent information can be retri…
Speech DereverberationDéréverbération non-supervisée de la parole par modèle hybride
This paper introduces a new training strategy to improve speech dereverberation systems in an unsupervised manner using only reverberant speech. Most existing algorithms rely on paired dry/reverberant data, which is diff…
Speech DereverberationVINP: Variational Bayesian Inference with Neural Speech Prior for Joint ASR-Effective Speech Dereverberation and Blind RIR Identification
Reverberant speech, denoting the speech signal degraded by the process of reverberation, contains crucial knowledge of both anechoic source speech and room impulse response (RIR). This work proposes a variational Bayesia…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Bayesian InferenceRoom Impulse Response (RIR)+3A Hybrid Model for Weakly-Supervised Speech Dereverberation
This paper introduces a new training strategy to improve speech dereverberation systems using minimal acoustic information and reverberant (wet) speech. Most existing algorithms rely on paired dry/wet data, which is diff…
modelSpeech DereverberationRun-Time Adaptation of Neural Beamforming for Robust Speech Dereverberation and Denoising
This paper describes speech enhancement for realtime automatic speech recognition (ASR) in real environments. A standard approach to this task is to use neural beamforming that can work efficiently in an online manner. I…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)DenoisingSpeech Dereverberation+3