https://github.com/amazingyyc/Brouhaha
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
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/amzoyang/CS-221-Final-Project
https://github.com/anastassia-b/neural-algorithm-artistic-style
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/andreser09/segan
https://github.com/andyljones/zonotable
https://github.com/anhkhoa039/Neural-Style-Transfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/anjalipemmaraju/styletransfernetwork
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/anthonysong98/super-mario-bros-ppo
https://github.com/anton-jeran/AV-RIR
https://github.com/anton-jeran/FAST-RIR
MESH2IR: Neural Acoustic Impulse Response Generator for Complex 3D Scenes
https://github.com/anton-jeran/Speech2RIR
https://github.com/anujdutt9/Artistic-Style-Transfer-using-Keras-Tensorflow
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/araffin/sbx
https://github.com/arnomoonens/yarll
https://github.com/aryan-mann/style-transfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/asadullah797/segan_impr
https://github.com/ashkanpakzad/atn
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/asraman9792/Image-Dehazing-GANS
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/audiolabs/torch-pesq
End-to-End Multi-Task Denoising for joint SDR and PESQ Optimization
https://github.com/automl/learna
https://github.com/bacnguyenne/ASR_LibriSpeech
Whispered-to-voiced Alaryngeal Speech Conversion with Generative Adversarial Networks
https://github.com/bay3s/ppo-parallel
https://github.com/bay3s/ppo-rl
https://github.com/benevolentAI/guacamol_baselines
https://github.com/benpetit/cs379c
https://github.com/bentrevett/pytorch-rl
https://github.com/bonniesjli/PPO-Reacher_UnityML
https://github.com/bonniesjli/PPO_Reacher
https://github.com/breizhn/tPLCnet
tPLCnet: Real-time Deep Packet Loss Concealment in the Time Domain Using a Short Temporal Context
https://github.com/brightyoun/Video-Style-Transfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/buddly27/stylish
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/canturan10/light_side
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/chainer/chainerrl
https://github.com/chanil1218/DCUnet.pytorch
https://github.com/chrismgeorge/Artistic_Additions_To_Style_Transfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/christiankellernc/styletransfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.