Papers with Code 아카이브

Speech Denoising

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 0
평가표: 2
보존된 평가 기록: 0

Obtain the clean speech of the target speaker by suppressing the background noise. Recent representative github platform ClearerVoice-Studio

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/IU-SAIGE/sparse_mle

공식 코드

Sparse Mixture of Local Experts for Efficient Speech Enhancement

https://github.com/NVIDIA/NeMo

공식 코드

Generative Speech Foundation Model Pretraining for High-Quality Speech Extraction and Restoration

https://github.com/SherifAbdulatif/CMGAN

공식 코드

CMGAN: Conformer-Based Metric-GAN for Monaural Speech Enhancement

https://github.com/Sindhu-Hegde/pseudo-visual-speech-denoising

공식 코드

Visual Speech Enhancement Without A Real Visual Stream

https://github.com/aleXiehta/WaveCRN

공식 코드

WaveCRN: An Efficient Convolutional Recurrent Neural Network for End-to-end Speech Enhancement

https://github.com/dreadbird06/tso_vace_wpe

공식 코드

Task-specific Optimization of Virtual Channel Linear Prediction-based Speech Dereverberation Front-End for Far-Field Speaker Verification

https://github.com/haoheliu/voicefixer

공식 코드

VoiceFixer: A Unified Framework for High-Fidelity Speech Restoration

https://github.com/haoxiangsnr/spiking-fullsubnet

공식 코드

Towards Ultra-Low-Power Neuromorphic Speech Enhancement with Spiking-FullSubNet

https://github.com/henryxrl/Listening-to-Sound-of-Silence-for-Speech-Denoising

공식 코드

Listening to Sounds of Silence for Speech Denoising

https://github.com/lab-emi/cleanumamba

공식 코드

CleanUMamba: A Compact Mamba Network for Speech Denoising using Channel Pruning

https://github.com/liqingchunnnn/only-noisy-training

공식 코드

Self-Supervised Speech Denoising Using Only Noisy Audio Signals

https://github.com/madhavmk/Noise2Noise-audio_denoising_without_clean_training_data

공식 코드

Speech Denoising Without Clean Training Data: A Noise2Noise Approach

https://github.com/microsoft/unilm

공식 코드

WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

https://github.com/modelscope/ClearerVoice-Studio

공식 코드

Monaural Speech Enhancement with Complex Convolutional Block Attention Module and Joint Time Frequency Losses

https://github.com/mosheman5/DNP

공식 코드

Speech Denoising by Accumulating Per-Frequency Modeling Fluctuations

https://github.com/nvidia/cleanunet

공식 코드

Speech Denoising in the Waveform Domain with Self-Attention

https://github.com/ruizhecao96/cmgan

공식 코드

CMGAN: Conformer-Based Metric-GAN for Monaural Speech Enhancement

https://github.com/sunwookimiub/BLSH

공식 코드

Boosted Locality Sensitive Hashing: Discriminative Binary Codes for Source Separation

https://github.com/tvuong123/ModulationDomainLoss

공식 코드

A Modulation-Domain Loss for Neural-Network-based Real-time Speech Enhancement

https://github.com/yluo42/fra-rir

공식 코드

FRA-RIR: Fast Random Approximation of the Image-source Method

https://github.com/youshanzhang/birdsoundsdenoising

공식 코드

BirdSoundsDenoising: Deep Visual Audio Denoising for Bird Sounds

https://github.com/Audio-WestlakeU/FullSubNet/blob/main/audio_zen/acoustics/rvb.py

Speech Dereverberation with a Reverberation Time Shortening Target

https://github.com/jonashaag/paperswithcode-speech-enhancement-audiosamples/tree/master/Phase-aware%20Single-stage%20Speech%20Denoising%20and%20Dereverberation%20with%20U-Net

Phase-aware Single-stage Speech Denoising and Dereverberation with U-Net

https://github.com/khalida1wwin/Noise2Noise-audio_denoising_without_clean_training_data

Speech Denoising Without Clean Training Data: A Noise2Noise Approach

https://github.com/kuntojirohan/speechdenoising

Speech Denoising with Deep Feature Losses

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.