https://github.com/SherifAbdulatif/CMGAN
공식 코드CMGAN: Conformer-Based Metric-GAN for Monaural Speech Enhancement
Papers with Code 아카이브
Audio Super-Resolution
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Audio super-resolution, especially speech, refers to the process of reconstructing high-resolution music signals from their low-resolution counterparts. Essentially, it enhances the quality of a speech signal by increasing its sampling rate or bandwidth while preserving naturalness and intelligibility. A representative Github project for speech super-resolution is ClearerVoice-Studio.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/aeromamba-super-resolution/aeromamba
공식 코드https://github.com/chomeyama/DualCycleGAN
공식 코드Nonparallel High-Quality Audio Super Resolution with Domain Adaptation and Resampling CycleGANs
https://github.com/haoheliu/ssr_eval
공식 코드https://github.com/jjunak-yun/FLowHigh_code
공식 코드FLowHigh: Towards Efficient and High-Quality Audio Super-Resolution with Single-Step Flow Matching
https://github.com/mindslab-ai/nuwave
공식 코드NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling
https://github.com/mindslab-ai/nuwave2
공식 코드NU-Wave 2: A General Neural Audio Upsampling Model for Various Sampling Rates
https://github.com/ml-postech/lisa
공식 코드Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution
https://github.com/ncarraz/AFILM
공식 코드https://github.com/nxtproduct/tunet
공식 코드https://github.com/ruizhecao96/cmgan
공식 코드CMGAN: Conformer-Based Metric-GAN for Monaural Speech Enhancement
https://github.com/serkansulun/deep-music-enhancer
공식 코드On Filter Generalization for Music Bandwidth Extension Using Deep Neural Networks
https://github.com/slp-rl/aero
공식 코드https://github.com/Amuzak-NTL/ASR-for-Speech-Recog
https://github.com/TrizteX/Audio-SuperRes
https://github.com/haoheliu/versatile_audio_super_resolution
https://github.com/johnathanchiu/audio-upsampling
https://github.com/kuleshov/audio-super-res
https://github.com/leolya/Audio-Super-Resolution-Tensorflow2.0-TFiLM
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations
https://github.com/maum-ai/nuwave
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling
https://github.com/maum-ai/nuwave2
NU-Wave 2: A General Neural Audio Upsampling Model for Various Sampling Rates
https://github.com/rishikksh20/NU-Wave-pytorch
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling
https://github.com/rishikksh20/NU-Wave2-pytorch
NU-Wave 2: A General Neural Audio Upsampling Model for Various Sampling Rates
https://github.com/serkansulun/deep-music-enhancement
On Filter Generalization for Music Bandwidth Extension Using Deep Neural Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.