Papers with Code 아카이브
Audio Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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Audio generation (synthesis) is the task of generating raw audio such as speech.
<span style="color:grey; opacity: 0.6">( Image credit: MelNet )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mostafaelaraby/wavegan-pytorch
https://github.com/multi-singer/multi-singer.github.io
Multi-Singer: Fast Multi-Singer Singing Voice Vocoder With A Large-Scale Corpus
https://github.com/myshell-ai/openvoice
https://github.com/nari-labs/dia
https://github.com/ndk03/Accent-Preserving-Voice-Cloning-using-SV2TTS/tree/master/Speech-Modeling-master
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
https://github.com/necrashter/SaShiMi-796
https://github.com/nicobernasconi/specgan
https://github.com/otosense/slang
https://github.com/outofculture/talk-like-me
https://github.com/paechi/wavegan-asr
https://github.com/pascalbakker/WaveNet-Implementation
https://github.com/pbrandl/aNN_Audio
https://github.com/peustr/wavenet
https://github.com/plachtaa/vall-e-x
https://github.com/ptillet/torch-blocksparse
https://github.com/pwc-1/Paper-9/tree/main/5/wavlm
https://github.com/r9y9/wavenet
https://github.com/rampage644/wavenet
https://github.com/randomrandom/deep-atrous-cnn-sentiment
https://github.com/rf5/diffwave-unconditional
https://github.com/rf5/simple-sashimi
https://github.com/rishikksh20/HiFiplusplus-pytorch
HiFi++: a Unified Framework for Bandwidth Extension and Speech Enhancement
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/royjames/room-impulse-responses
dEchorate: a Calibrated Room Impulse Response Database for Echo-aware Signal Processing
https://github.com/scpark20/universal-music-translation
https://github.com/serkansulun/deep-music-enhancement
On Filter Generalization for Music Bandwidth Extension Using Deep Neural Networks
https://github.com/serp-ai/bark-with-voice-clone
https://github.com/sh-lee-prml/BigVGAN
BigVGAN: A Universal Neural Vocoder with Large-Scale Training
https://github.com/sh-lee-prml/hierspeechpp
BigVGAN: A Universal Neural Vocoder with Large-Scale Training
https://github.com/sh-lee-prml/periodwave
BigVGAN: A Universal Neural Vocoder with Large-Scale Training
https://github.com/shinjiwlab/versa
ESPnet-Codec: Comprehensive Training and Evaluation of Neural Codecs for Audio, Music, and Speech
https://github.com/smoke-trees/Voice-synthesis
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
https://github.com/snap-research/GenAU
https://github.com/sriharireddypusapati/speech-to-text-wavenet2
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.