Speech Enhancement

Speech Enhancement is a signal processing task that involves improving the quality of speech signals captured under noisy or degraded conditions. The goal of speech enhancement is to make speech signals clearer, more intelligible, and more pleasant to listen to, which can be used for various applications such as voice recognition, teleconferencing, and hearing aids. ( Image credit: A Fully Convolutional Neural Network For Speech Enhancement )

Benchmarks

Libraries

Datasets

Subtasks

Most implemented papers

Proximal Policy Optimization Algorithms

Content

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

SEGAN: Speech Enhancement Generative Adversarial Network

Phase-aware Speech Enhancement with Deep Complex U-Net

DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement

A Fully Convolutional Neural Network for Speech Enhancement

Fullsubnet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement

MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement

SoundStream: An End-to-End Neural Audio Codec