https://github.com/christopher-beckham/annotated-conditional-diffusion
Conditional Diffusion Probabilistic Model for Speech Enhancement
Papers with Code 아카이브
Speech Enhancement
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 18
- 보존된 평가 기록
- 122
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. A representative Github project with online demo : ClearerVoice-Studio.
<span style="color:grey; opacity: 0.6">( Image credit: A Fully Convolutional Neural Network For Speech Enhancement )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/chuanli11/MGANs
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/cipher982/ppo-exploration
https://github.com/clwainwright/proximal_policy_optimization
https://github.com/cookcodes/percepnet
A Perceptually-Motivated Approach for Low-Complexity, Real-Time Enhancement of Fullband Speech
https://github.com/craigmacartney/Wave-U-Net-For-Speech-Enhancement
https://github.com/cryu854/FastStyle
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/cuiziteng/iccv_maet
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/cuiziteng/maet
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/cyhuang-tw/robust-vc
https://github.com/danedane-haider/HybrA-filterbanks
Hold Me Tight: Stable Encoder-Decoder Design for Speech Enhancement
https://github.com/danelee2601/rl-based-automatic-berthing
https://github.com/deNsuh/segan-pytorch
https://github.com/decoderkurt/research_project_school_of_ai_2019
https://github.com/deconlabs/Binanace-trading-simulation
https://github.com/deconlabs/Binanace_trading_simulation
https://github.com/deconlabs/TradingZoo-Dynamic-fee-simulation
https://github.com/develooper1994/MasterThesis
https://github.com/dickreuter/neuron_poker
https://github.com/dkoleber/multi_style_transfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/dmiu-shell/deeprl-shell
https://github.com/donamin/llc
https://github.com/donghoney0416/DeFT-AN
DeFT-AN: Dense Frequency-Time Attentive Network for Multichannel Speech Enhancement
https://github.com/downingbots/RLDonkeycar
https://github.com/dxyang/styletransfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/dyabel/handson_rl
https://github.com/eladsar/rbi
https://github.com/emerge-lab/nocturne_lab
https://github.com/etttttte/mayfest2018
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/evieq01/oodil
https://github.com/facebookresearch/Horizon
https://github.com/facebookresearch/ReAgent
https://github.com/facebookresearch/svoice
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation
https://github.com/fakufaku/diffusion-separation
https://github.com/fdcl-gwu/gym-rotor
https://github.com/francoisgermain/SpeechDenoisingWithDeepFeatureLosses
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.