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Audio-Visual Speech Recognition

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하위 태스크: 1
평가표: 4
보존된 평가 기록: 24

Audio-visual speech recognition is the task of transcribing a paired audio and visual stream into text.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/wataru-nakata/fastspeech2-jsut

FastSpeech 2: Fast and High-Quality End-to-End Text to Speech

https://github.com/wenet-e2e/wetts

Unified Mandarin TTS Front-end Based on Distilled BERT Model

https://github.com/wesbz/SoundStream

SoundStream: An End-to-End Neural Audio Codec

https://github.com/xcmyz/FastSpeech

FastSpeech: Fast, Robust and Controllable Text to Speech

https://github.com/yanggeng1995/EATS

End-to-End Adversarial Text-to-Speech

https://github.com/yanggeng1995/FB-MelGAN

Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram

https://github.com/yanggeng1995/GAN-TTS

High Fidelity Speech Synthesis with Adversarial Networks

https://github.com/yangyucheng000/University/tree/main/model-2/fastspeech2_conformer

FastSpeech 2: Fast and High-Quality End-to-End Text to Speech

https://github.com/yangyucheng000/University/tree/main/model-3/seamless_m4t

SeamlessM4T: Massively Multilingual & Multimodal Machine Translation

https://github.com/yebiny/DepthOfAnaesthesia_eeg

WaveNet: A Generative Model for Raw Audio

https://github.com/yistLin/FragmentVC

Robust universal neural vocoding

https://github.com/yistlin/universal-vocoder

Robust universal neural vocoding

https://github.com/yl4579/StyleTTS2

Phoneme-Level BERT for Enhanced Prosody of Text-to-Speech with Grapheme Predictions

https://github.com/yl4579/pl-bert

Phoneme-Level BERT for Enhanced Prosody of Text-to-Speech with Grapheme Predictions

https://github.com/ylacombe/dataspeech

Natural language guidance of high-fidelity text-to-speech with synthetic annotations

https://github.com/yoshifumi-nakano/visual-text-to-speech

FastSpeech 2: Fast and High-Quality End-to-End Text to Speech

https://github.com/yxlu-0102/MP-SENet

Source-Filter-Based Generative Adversarial Neural Vocoder for High Fidelity Speech Synthesis

https://github.com/zain-jiang/speech-editing-toolkit

EditSpeech: A Text Based Speech Editing System Using Partial Inference and Bidirectional Fusion

https://github.com/zengchang233/xiaoicesing2

HiFi-WaveGAN: Generative Adversarial Network with Auxiliary Spectrogram-Phase Loss for High-Fidelity Singing Voice Generation

https://github.com/zhangbo2008/fastSpeeck2_chinese_train

FastSpeech 2: Fast and High-Quality End-to-End Text to Speech

https://github.com/zhong110020/Tensorflow-TCN

WaveNet: A Generative Model for Raw Audio

https://github.com/zhong110020/keras-tcn

WaveNet: A Generative Model for Raw Audio

https://github.com/zll1996/TCN

WaveNet: A Generative Model for Raw Audio

https://github.com/zziz/pwc

End-to-end Audio-visual Speech Recognition with Conformers

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.