https://github.com/soham97/pam
Evaluating Speech Synthesis by Training Recognizers on Synthetic Speech
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/soobinseo/transformer-tts
https://github.com/sriharireddypusapati/speech-to-text-wavenet2
https://github.com/stdereka/liverpool-ion-switching
https://github.com/stepfun-ai/step-audio
Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Model
https://github.com/sunilrdvg/ESOLA
Epoch-Synchronous Overlap-Add (ESOLA) for Time- and Pitch-Scale Modification of Speech Signals
https://github.com/suno-ai/bark
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
https://github.com/swasun/VQ-VAE-Speech
https://github.com/swatsw/isg_official
https://github.com/syang1993/gst-tacotron
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
https://github.com/takaaki-saeki/ssl_speech_restoration
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
https://github.com/tarepan/jsss
JSSS: free Japanese speech corpus for summarization and simplification
https://github.com/tarepan/jsut
JSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis
https://github.com/tartunlp/transformertts
https://github.com/text-to-audio/make-an-audio
ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speech
https://github.com/thepowerfuldeez/tacotron2
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/thethirdwheel/malumagraph
https://github.com/thorwhalen/sla
https://github.com/thorwhalen/slang
https://github.com/thuhcsi/tacotron
https://github.com/tigthor/Voice-Cloning-AI
https://github.com/trinhtuanvubk/diff-vc
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
https://github.com/ucsd-dsc-arts/dsc160-final-dsc160-final-group19
https://github.com/vicky-hnk/time-flex
https://github.com/vincentherrmann/pytorch-wavenet
https://github.com/vincenzo-scotti/tacotron2
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/vinusankars/ESOLA
Epoch-Synchronous Overlap-Add (ESOLA) for Time- and Pitch-Scale Modification of Speech Signals
https://github.com/vohoaiviet/voice-vector
https://github.com/wataru-nakata/fastspeech2-jsut
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/weilinie/JARE
Towards a Better Understanding and Regularization of GAN Training Dynamics
https://github.com/whisperspeech/whisperspeech
https://github.com/xcmyz/FastSpeech
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/xinleiniu/latentoptimalpathsbayesiandp
RyanSpeech: A Corpus for Conversational Text-to-Speech Synthesis
https://github.com/xinshengwang/Tacotron-pytorch
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/yanggeng1995/EATS
https://github.com/yanggeng1995/FB-MelGAN
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.