https://github.com/racai-ai/TEPROLIN
Tools and resources for Romanian text-to-speech and speech-to-text applications
Papers with Code 아카이브
Accented Speech Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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
https://github.com/raotnameh/End-to-end-E2E-Named-Entity-Recognition-from-English-Speech
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/raraz15/DeepTurkish
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/rarefin/TTS_VAE
Hierarchical Generative Modeling for Controllable Speech Synthesis
https://github.com/revsic/jax-variational-diffwave
https://github.com/revsic/tf-diffwave
https://github.com/revsic/torch-diffusion-wavegan
https://github.com/rf5/diffwave-unconditional
https://github.com/rhoposit/MOS_Estimation
https://github.com/rhoposit/MOS_Estimation2
https://github.com/richardbaihe/a3t
A$^3$T: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and Editing
https://github.com/rickyHong/ClariNet-WaveNet-repl
ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech
https://github.com/rickyHong/GAN-TTS-repl2
Statistical Parametric Speech Synthesis Incorporating Generative Adversarial Networks
https://github.com/rickyHong/GANTTS-update-repl
Statistical Parametric Speech Synthesis Incorporating Generative Adversarial Networks
https://github.com/rickyHong/OpenSeq2Seq-repl
Mixed-Precision Training for NLP and Speech Recognition with OpenSeq2Seq
https://github.com/rickyHong/gantts-update-repl2
Statistical Parametric Speech Synthesis Incorporating Generative Adversarial Networks
https://github.com/rishikksh20/FastSpeech2
https://github.com/rishikksh20/HiFi-GAN
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
https://github.com/rishikksh20/LightSpeech
https://github.com/rishikksh20/TalkNet2-pytorch
https://github.com/rishikksh20/UnivNet-pytorch
https://github.com/rishikksh20/VocGAN
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
https://github.com/rishikksh20/iSTFTNet-pytorch
https://github.com/rishikksh20/melgan
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
https://github.com/rishikksh20/tfgan
https://github.com/robmsmt/KerasDeepSpeech
https://github.com/roedoejet/fastspeech2
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/roedoejet/fastspeech2_acl2022_reproducibility
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/rongjiehuang/transpeech
GenerSpeech: Towards Style Transfer for Generalizable Out-Of-Domain Text-to-Speech
https://github.com/rosinality/melgan-pytorch
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/s3nh/pytorch-tacotron2
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.