Speech Enhancement

SERGAN: Speech Enhancement using Relativistic Generative Adversarial Networks with Gradient Penalty

Popular neural network-based speech enhancement systems operate on the magnitude spectrogram and ignore the phase mismatch between the noisy and clean speech signals. Recently, conditional generative adversarial networks (cGANs) have shown promise in …

iSEGAN

Tricks to improve SEGAN performance. Eveything is re-implemented into Keras with Tensorflow backend.

SERGAN: Speech enhancement relativistic generative adversarial network

A fully convolutional end-to-end speech enhancement system with GANs

Biophysically-inspired Features Improve the Generalizability of Neural Network-based Speech Enhancement Systems

Recent advances in neural network (NN)-based speech enhancement schemes are shown to outperform most conventional techniques. However, the performance of such systems in adverse listening conditions such as negative signal-to-noise ratios and unseen …

Joint Denoising and Dereverberation Using Exemplar-Based Sparse Representations and Decaying Norm Constraint

Exemplar-based nonnegative models, where the noisy speech is decomposed as a sparse nonnegative linear combination of the speech and noise exemplars stored in a dictionary, have been successfully used for speech denoising. This paper extends this …

Joint dereverberation and denoising using NMD

MATLAB impelementation of a joint dereverberation and denoising algorithm based on non-negative matrix deconvolution

Supervised Speech Dereverberation in Noisy Environments using Exemplar-based Sparse Representations

Exemplar-based techniques, where the noisy speech is decomposed as a linear combination of the speech and noise exemplars stored in a dictionary, have been successfully used for speech enhancement in noisy environments. This paper extends this …

Coupled Dictionaries for Exemplar-Based Speech Enhancement and Automatic Speech Recognition

Exemplar-based speech enhancement systems work by decomposing the noisy speech as a weighted sum of speech and noise exemplars stored in a dictionary and use the resulting speech and noise estimates to obtain a time-varying filter in the …

Noise robust exemplar matching with coupled dictionaries for single-channel speech enhancement

In this paper, we propose a single-channel speech enhancement system based on the noise robust exemplar matching (N-REM) framework using coupled dictionaries. N-REM approximates noisy speech segments as a sparse linear combination of speech and noise …

Exemplar-based speech enhancement for deep neural network based automatic speech recognition

Deep neural network (DNN) based acoustic modelling has been successfully used for a variety of automatic speech recognition (ASR) tasks, thanks to its ability to learn higher-level information using multiple hidden layers. This paper investigates the …