https://github.com/Text-to-Audio/AudioLCM
ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speech
Papers with Code 아카이브
Speech Recognition
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Speech Recognition is the task of converting spoken language into text. It involves recognizing the words spoken in an audio recording and transcribing them into a written format. The goal is to accurately transcribe the speech in real-time or from recorded audio, taking into account factors such as accents, speaking speed, and background noise.
<span style="color:grey; opacity: 0.6">( Image credit: SpecAugment )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ThisuriLekamge/Stock-Price-Prediction-on-Bitcoin-trading-data-using-LSTM-with-PyTorch
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
https://github.com/TinfoilHat0/Defending-Against-Backdoors-with-Robust-Learning-Rate
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/TomVeniat/SANAS
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
https://github.com/TsingZ0/FL-IoT
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/TsingZ0/PFL-Non-IID
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/TsuchiyaYutaro/federated_learning_note
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/Tushar-ml/ED-CEC
https://github.com/UESBTC/DenseNet-Tensorflow
https://github.com/UlionTse/mlgb
https://github.com/UnofficialJuliaMirror/DeepMark-deepmark
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/UnofficialJuliaMirrorSnapshots/DeepMark-deepmark
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/VP-0822/Video-Keyword-Extractor
https://github.com/Vamshi399/CarND-Vehicle-Detection
https://github.com/Vernacular-ai/Multimodal-Slu
TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech
https://github.com/Vikas-Sony/speech-to-text
https://github.com/Vill-Lab/2023-TMM-Grad-SAS
Unified Streaming and Non-streaming Two-pass End-to-end Model for Speech Recognition
https://github.com/VinayBN8997/CIFAR-10-object-detection
https://github.com/Vladimetr/ASR-Knowledge-Transferring
CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition
https://github.com/WLM1ke/poptimizer
https://github.com/WalterJohnson0/DeepSpeech-KerasRebuild
https://github.com/WelkinYang/GradTTS
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
https://github.com/WenwanChen/pvad
https://github.com/WindQAQ/listen-attend-and-spell
https://github.com/WorldBestProgrammer/KoSpeech
KoSpeech: Open-Source Toolkit for End-to-End Korean Speech Recognition
https://github.com/Yeeun-Lee/parrot_proj1
https://github.com/Yeeun-Lee/parrot_vision_competition
https://github.com/YerevaNN/DIIN-in-Keras
https://github.com/Yindong-Zhang/GraphConvolutionDrugTargetInteration
https://github.com/YiwenShaoStephen/NGD-SGD
Parallel training of DNNs with Natural Gradient and Parameter Averaging
https://github.com/YixuanLi/densenet-tensorflow
https://github.com/YoungloLee/tf2-speech-recognition-transformer
https://github.com/YuBeomGon/DeepSpeech
https://github.com/YuanPJ/Voice-in-ASR
https://github.com/YuvalBecker/MelNet
MelNet: A Generative Model for Audio in the Frequency Domain
https://github.com/YuvalBecker/MelNet-Tensorflow
MelNet: A Generative Model for Audio in the Frequency Domain
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.