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Visual Speech Recognition
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/JeongHun0716/MMS-LLaMA
공식 코드MMS-LLaMA: Efficient LLM-based Audio-Visual Speech Recognition with Minimal Multimodal Speech Tokens
https://github.com/JeongHun0716/zero-avsr
공식 코드https://github.com/KAIST-AILab/SyncVSR
공식 코드https://github.com/Rudrabha/Lip2Wav
공식 코드Learning Individual Speaking Styles for Accurate Lip to Speech Synthesis
https://github.com/ahaliassos/lipforensics
공식 코드Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery Detection
https://github.com/ahaliassos/raven
공식 코드Jointly Learning Visual and Auditory Speech Representations from Raw Data
https://github.com/choijeongsoo/lip2speech-unit
공식 코드https://github.com/chris10m/lip2speech
공식 코드https://github.com/circleredrain/avger
공식 코드Listening and Seeing Again: Generative Error Correction for Audio-Visual Speech Recognition
https://github.com/cyanbx/FastLTS
공식 코드FastLTS: Non-Autoregressive End-to-End Unconstrained Lip-to-Speech Synthesis
https://github.com/dalision/modalbiasavsr
공식 코드https://github.com/david-gimeno/evaluating-end2end-spanish-lipreading
공식 코드Evaluation of End-to-End Continuous Spanish Lipreading in Different Data Conditions
https://github.com/david-gimeno/lip-rtve
공식 코드LIP-RTVE: An Audiovisual Database for Continuous Spanish in the Wild
https://github.com/david-gimeno/tailored-avsr
공식 코드Tailored Design of Audio-Visual Speech Recognition Models using Branchformers
https://github.com/espnet/espnet
공식 코드https://github.com/exgc/avmust-ted
공식 코드https://github.com/exgc/opensr
공식 코드OpenSR: Open-Modality Speech Recognition via Maintaining Multi-Modality Alignment
https://github.com/facebookresearch/av_hubert
공식 코드https://github.com/facebookresearch/muavic
공식 코드https://github.com/georgesterpu/Sigmedia-AVSR
공식 코드How to Teach DNNs to Pay Attention to the Visual Modality in Speech Recognition
https://github.com/georgesterpu/Taris
공식 코드https://github.com/hltchkust/ci-avsr
공식 코드CI-AVSR: A Cantonese Audio-Visual Speech Dataset for In-car Command Recognition
https://github.com/humanmllm/cogenav
공식 코드CoGenAV: Versatile Audio-Visual Representation Learning via Contrastive-Generative Synchronization
https://github.com/iip-sogang/olkavs-avspeech
공식 코드OLKAVS: An Open Large-Scale Korean Audio-Visual Speech Dataset
https://github.com/jasonppy/promptingwhisper
공식 코드Prompting the Hidden Talent of Web-Scale Speech Models for Zero-Shot Task Generalization
https://github.com/jeonghun0716/visual-speech-recognition-for-low-resource-languages
공식 코드https://github.com/jxzhanggg/DistillAV
공식 코드Audio-Visual Representation Learning via Knowledge Distillation from Speech Foundation Models
https://github.com/liu12366262626/alignvsr
공식 코드AlignVSR: Audio-Visual Cross-Modal Alignment for Visual Speech Recognition
https://github.com/liuzhuang13/DenseNet
공식 코드https://github.com/lumia-group/leveraging-self-supervised-learning-for-avsr
공식 코드Leveraging Unimodal Self-Supervised Learning for Multimodal Audio-Visual Speech Recognition
https://github.com/midas-research/DECA
공식 코드Harnessing GANs for Zero-shot Learning of New Classes in Visual Speech Recognition
https://github.com/mispchallenge/misp-icme-avsr
공식 코드https://github.com/mkt-dataoceanai/cnvsrc2023baseline
공식 코드The NPU-ASLP-LiAuto System Description for Visual Speech Recognition in CNVSRC 2023
https://github.com/mpc001/Visual_Speech_Recognition_for_Multiple_Languages
공식 코드Visual Speech Recognition for Multiple Languages in the Wild
https://github.com/mpc001/auto_avsr
공식 코드Auto-AVSR: Audio-Visual Speech Recognition with Automatic Labels
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.