https://github.com/modelscope/FunCodec
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT
Papers with Code 아카이브
Speech Synthesis
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 15
- 평가표
- 5
- 보존된 평가 기록
- 31
Speech synthesis is the task of generating speech from some other modality like text, lip movements etc.
Please note that the leaderboards here are not really comparable between studies - as they use mean opinion score as a metric and collect different samples from Amazon Mechnical Turk.
<span style="color:grey; opacity: 0.6">( Image credit: WaveNet: A generative model for raw audio )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mozilla/TTS
https://github.com/mtresearcher/FastSpeech2
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/mukeshv0/ParallelWaveGAN
https://github.com/nafiuny/ICRCycleGAN-VC
Statistical Parametric Speech Synthesis Incorporating Generative Adversarial Networks
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/neillu23/DiffuSE
https://github.com/nickovchinnikov/tts-framework
DelightfulTTS: The Microsoft Speech Synthesis System for Blizzard Challenge 2021
https://github.com/noetits/ICE-Talk
https://github.com/nvcnet/nvcnet.github.io
https://github.com/otosense/slang
https://github.com/outofculture/talk-like-me
https://github.com/ozora-ogino/LCNN
https://github.com/pascalbakker/WaveNet-Implementation
https://github.com/pbrandl/aNN_Audio
https://github.com/peustr/wavenet
https://github.com/philsyn/diffwave-unconditional
https://github.com/philsyn/diffwave-vocoder
https://github.com/plachtaa/vall-e-x
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
https://github.com/playvoice/grad-svc
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
https://github.com/pranaymanocha/PerceptualAudio
https://github.com/prijatelj/crowd_noise
https://github.com/pwc-1/Paper-10/tree/main/seamless_m4t
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
https://github.com/pwc-1/Paper-10/tree/main/speecht5
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/pwc-1/Paper-9/tree/main/5/wavlm
https://github.com/r9y9/deepvoice3_pytorch
Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning
https://github.com/r9y9/gantts
Statistical Parametric Speech Synthesis Incorporating Generative Adversarial Networks
https://github.com/r9y9/tacotron_pytorch
https://github.com/r9y9/wavenet
https://github.com/racai-ai/ROBINDialog
Tools and resources for Romanian text-to-speech and speech-to-text applications
https://github.com/racai-ai/TEPROLIN
Tools and resources for Romanian text-to-speech and speech-to-text applications
https://github.com/racai-ai/srla
Tools and resources for Romanian text-to-speech and speech-to-text applications
https://github.com/racai-ai/ssla
Tools and resources for Romanian text-to-speech and speech-to-text applications
https://github.com/racinmat/lecture-generator
https://github.com/rampage644/wavenet
https://github.com/randomrandom/deep-atrous-cnn-sentiment
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.