https://github.com/martinlenglet/avtacotron2
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
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/mary-phuong/multiexit-distillation
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges
https://github.com/marynader6/espnetV.8
Improved training of end-to-end attention models for speech recognition
https://github.com/marynader6/transformerTTS
Improved training of end-to-end attention models for speech recognition
https://github.com/mashrurmorshed/torch-kwt
Keyword Transformer: A Self-Attention Model for Keyword Spotting
https://github.com/maum-ai/phaseaug
PhaseAug: A Differentiable Augmentation for Speech Synthesis to Simulate One-to-Many Mapping
https://github.com/maum-ai/univnet
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
https://github.com/maum-ai/voicefilter
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking
https://github.com/maum-ai/wavegrad2
https://github.com/max-andr/joint-cnn-mrf
Learning Human Pose Estimation Features with Convolutional Networks
https://github.com/mdangschat/speech-corpus-dl
TED-LIUM 3: twice as much data and corpus repartition for experiments on speaker adaptation
https://github.com/meiyor/SincNet-for-Autism-EEG-based-Emotion-Recognition
Speech and Speaker Recognition from Raw Waveform with SincNet
https://github.com/mejanvijay/RNN-Transducer
https://github.com/michaeltrs/Lipreading_ResNet_LSTM
https://github.com/michelle0924hhx/DiffPrivate_FedLearning
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/microsoft/torchscale
https://github.com/midusi/cacic2019-handshapes
https://github.com/mikudehuane/Federated-Averaging
Communication-Efficient Learning of Deep Networks from Decentralized Data
https://github.com/mimbres/yourmt3
https://github.com/mindmapper15/Voice-Converter
https://github.com/mindslab-ai/univnet
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
https://github.com/mindslab-ai/voicefilter
VoiceFilter-Lite: Streaming Targeted Voice Separation for On-Device Speech Recognition
https://github.com/mindslab-ai/wavegrad2
https://github.com/mindspore-ai/models/tree/master/official/audio/lpcnet
A Real-Time Wideband Neural Vocoder at 1.6 kb/s Using LPCNet
https://github.com/mindspore-ai/models/tree/master/official/audio/melgan
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
https://github.com/mindspore-ai/models/tree/master/official/cv/densenet
https://github.com/mindspore-ai/models/tree/master/official/cv/warpctc
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/mindspore-ai/models/tree/master/research/audio/deepspeech2
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/mindspore-ai/models/tree/master/research/audio/tacotron2
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/mindspore-ai/models/tree/master/research/audio/wavenet
https://github.com/mindspore-courses/DeepNLP-models-MindSpore
A Simple Way to Initialize Recurrent Networks of Rectified Linear Units
https://github.com/mindspore-courses/MindSpore-classification
https://github.com/mindspore-courses/heads-on-mindspore/tree/main/4-neural_poet_RNN
A Critical Review of Recurrent Neural Networks for Sequence Learning
https://github.com/mindspore-courses/heads-on-mindspore/tree/main/6-speech_recognition
Joint CTC-Attention based End-to-End Speech Recognition using Multi-task Learning
https://github.com/mindspore-ecosystem/mindcv/blob/main/mindcv/models/densenet.py
https://github.com/minggli/DenseNet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.