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/baidu-research/warp-ctc
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/barronalex/Tacotron
https://github.com/basveeling/wavenet
https://github.com/benmoseley/simple-wavenet
https://github.com/bigpon/QPPWG
https://github.com/bigpon/vcc20_baseline_cyclevae
https://github.com/bjtommychen/Keras_DeepSpeech2_SpeechRecognition
https://github.com/bloodraven66/deepforcedaligner
https://github.com/bossemel/NAF-Python3
https://github.com/bradyneal/causal-benchmark
https://github.com/bradyneal/realcause
https://github.com/brightlaboratory/polydl
PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives
https://github.com/bshall/Tacotron
Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis
https://github.com/cadia-lvl/fastspeech2
https://github.com/caillonantoine/waveflow
https://github.com/cchinchristopherj/Concert-of-Whales
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
https://github.com/cecile-hi/regularized-adaptive-weight-modification
What to Remember: Self-Adaptive Continual Learning for Audio Deepfake Detection
https://github.com/choiHkk/Transformer-TTS
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/christopher-beckham/annotated-conditional-diffusion
Conditional Diffusion Probabilistic Model for Speech Enhancement
https://github.com/ciaua/score_lyrics_free_svg
https://github.com/cnlinxi/style-token_tacotron2
Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis
https://github.com/codetendolkar/tacotron-2-explained
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/collabora/whisperspeech
https://github.com/coreyoconnor/tensorderp
https://github.com/cosmoquester/speech-recognition
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
https://github.com/creotiv/RussianTTS-Tacotron2
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/cyhuang-tw/speechcaps
PromptTTS: Controllable Text-to-Speech with Text Descriptions
https://github.com/dada-bots/dadabots_sampleRNN
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
https://github.com/daniilrobnikov/vits2
YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone
https://github.com/danoneata/xts
https://github.com/dathudeptrai/TensorflowTTS
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
https://github.com/deciding/ParallelWaveGAN
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
https://github.com/deepsound-project/samplernn-pytorch
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
https://github.com/dhgrs/chainer-ClariNet
ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech
https://github.com/dipjyoti92/SC-WaveRNN
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.