Lipreading
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Lipreading is a process of extracting speech by watching lip movements of a speaker in the absence of sound. Humans lipread all the time without even noticing. It is a big part in communication albeit not as dominant as audio. It is a very helpful skill to learn especially for those who are hard of hearing.
Deep Lipreading is the process of extracting speech from a video of a silent talking face using deep neural networks. It is also known by few other names: Visual Speech Recognition (VSR), Machine Lipreading, Automatic Lipreading etc.
The primary methodology involves two stages: i) Extracting visual and temporal features from a sequence of image frames from a silent talking video ii) Processing the sequence of features into units of speech e.g. characters, words, phrases etc. We can find several implementations of this methodology either done in two separate stages or trained end-to-end in one go.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/JackSyu/Discriminative-Multi-modality-Speech-Recognition
공식 코드https://github.com/KAIST-AILab/SyncVSR
공식 코드https://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/ahaliassos/usr
공식 코드Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual Inputs
https://github.com/amourwaltz/bayeslms
공식 코드Bayesian Neural Network Language Modeling for Speech Recognition
https://github.com/david-gimeno/evaluating-end2end-spanish-lipreading
공식 코드Evaluation of End-to-End Continuous Spanish Lipreading in Different Data Conditions
https://github.com/facebookresearch/av_hubert
공식 코드https://github.com/jxzhanggg/DistillAV
공식 코드Audio-Visual Representation Learning via Knowledge Distillation from Speech Foundation Models
https://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/mpc001/Lipreading_using_Temporal_Convolutional_Networks
공식 코드Towards Practical Lipreading with Distilled and Efficient Models
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
https://github.com/perathambkk/lipreading
공식 코드SpotFast Networks with Memory Augmented Lateral Transformers for Lipreading
https://github.com/rizkiarm/LipNet
공식 코드https://github.com/rkmtlab/LipLearner
공식 코드LipLearner: Customizable Silent Speech Interactions on Mobile Devices
https://github.com/sailordiary/deep-face-vsr
공식 코드Can We Read Speech Beyond the Lips? Rethinking RoI Selection for Deep Visual Speech Recognition
https://github.com/sally-sh/vsp-llm
공식 코드https://github.com/tstafylakis/Lipreading-ResNet
공식 코드https://github.com/xing96/MIM-lipreading
공식 코드https://github.com/Abishalini/LipReadingGUI
https://github.com/Fengdalu/LipNet-PyTorch
https://github.com/Fengdalu/Lipreading-DenseNet3D
LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild
https://github.com/JackSyu/AE-MSR
https://github.com/LiZhenghua0311/lip
https://github.com/NirHeaven/D3D
LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild
https://github.com/Oguzhanercan/Vision-Transformers
https://github.com/PatrickPrakash/LiptoSpeech
https://github.com/PlatDrake2875/LipNet
https://github.com/SMIL-SPCRAS/AVCRFormer
https://github.com/SohaibAnwaar/lip-Reading-by-Deep-learning
https://github.com/Yondijr/FlowerPower
https://github.com/amitai1992/AutomatedLipReading
https://github.com/around-star/Speech-Recognition
Recurrent Neural Network Transducer for Audio-Visual Speech Recognition
https://github.com/david-gimeno/lip-rtve
Visual Speech Recognition for Multiple Languages in the Wild
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.