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/2023-MindSpore-1/ms-code-57
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/2023-MindSpore-1/ms-code-63
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/2023-MindSpore-1/ms-code-74
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
https://github.com/2023-MindSpore-4/Code-5/tree/main/IntegralNeuralNetworks
fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/fastspeech2_conformer
FastSpeech 2: Fast and High-Quality End-to-End Text to Speech
https://github.com/2noise/chattts
Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
https://github.com/AI-Huang/WaveNet
https://github.com/ANLGBOY/WaveNODE
WaveNODE: A Continuous Normalizing Flow for Speech Synthesis
https://github.com/AmirmohammadRostami/ASV-anti-spoofing-with-EABN
EfficientNet-Absolute Zero for Continuous Speech Keyword Spotting
https://github.com/Baichenjia/Tensorflow-TCN
https://github.com/Berthaniu/LatentOptimalPathsBayesianDP
RyanSpeech: A Corpus for Conversational Text-to-Speech Synthesis
https://github.com/BogiHsu/Tacotron2-PyTorch
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/CODEJIN/GST_Tacotron
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
https://github.com/Chasm4359/ProTS
https://github.com/ClorverCcy/GEDLoss_pytorch
https://github.com/CorentinJ/Real-Time-Voice-Cloning
https://github.com/CorrelAid/codingchallenge1020_team1
https://github.com/DeepMark/deepmark
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/DevonFulcher/CryptoPricePredictor
https://github.com/Digital-Umuganda/Deepspeech-Kinyarwanda
https://github.com/DomhnallBoyle/sv2s
https://github.com/Edresson/ZS-TTS-Evaluation
https://github.com/FazedAI/OpenSeq2Seq
Mixed-Precision Training for NLP and Speech Recognition with OpenSeq2Seq
https://github.com/GNovich/Talk2Me
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
https://github.com/GPUPhobia/vocal-mask
https://github.com/Gal1eo/DT2119
https://github.com/GavinGuan95/Punctuator.Pytorch
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/GeorgeFedoseev/DeepSpeech
https://github.com/HaiFengZeng/clari_wavenet_vocoder
https://github.com/HsiehKang/wavenet/blob/main/wavenet.ipynb
https://github.com/IAHispano/Applio
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
https://github.com/IAHispano/Applio/tree/exp/vocoders/rvc/lib/algorithm
BigVGAN: A Universal Neural Vocoder with Large-Scale Training
https://github.com/IBM/MAX-Speech-to-Text-Converter
https://github.com/IvKosar/text2speech
https://github.com/Jeevesh8/Cross-Lingual-Voice-Cloning
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.