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.
논문
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UniCUE: Unified Recognition and Generation Framework for Chinese Cued Speech Video-to-Speech Generation
OXSeg: Multidimensional attention UNet-based lip segmentation using semi-supervised lip contours
Target Speaker Lipreading by Audio-Visual Self-Distillation Pretraining and Speaker Adaptation
Audio-Visual Representation Learning via Knowledge Distillation from Speech Foundation Models
Evaluation of End-to-End Continuous Spanish Lipreading in Different Data Conditions
Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual Inputs
RAL:Redundancy-Aware Lipreading Model Based on Differential Learning with Symmetric Views
SyncVSR: Data-Efficient Visual Speech Recognition with End-to-End Crossmodal Audio Token Synchronization
Watch Your Mouth: Silent Speech Recognition with Depth Sensing
Enhancing Lip Reading with Multi-Scale Video and Multi-Encoder
Where Visual Speech Meets Language: VSP-LLM Framework for Efficient and Context-Aware Visual Speech Processing
Cross-Attention Fusion of Visual and Geometric Features for Large Vocabulary Arabic Lipreading
Analysis of Visual Features for Continuous Lipreading in Spanish
Investigating the dynamics of hand and lips in French Cued Speech using attention mechanisms and CTC-based decoding
Audio-Visual Speech Enhancement with Score-Based Generative Models
Word-level Persian Lipreading Dataset
Auto-AVSR: Audio-Visual Speech Recognition with Automatic Labels
Conformers are All You Need for Visual Speech Recognition
LipLearner: Customizable Silent Speech Interactions on Mobile Devices
LipFormer: Learning to Lipread Unseen Speakers based on Visual-Landmark Transformers
Jointly Learning Visual and Auditory Speech Representations from Raw Data
Relaxed Attention for Transformer Models
Training Strategies for Improved Lip-reading
Visual Speech Recognition in a Driver Assistance System
Bayesian Neural Network Language Modeling for Speech Recognition
Towards MOOCs for Lipreading: Using Synthetic Talking Heads to Train Humans in Lipreading at Scale
Lip-Listening: Mixing Senses to Understand Lips using Cross Modality Knowledge Distillation for Word-Based Models
Is Lip Region-of-Interest Sufficient for Lipreading?
Accurate and Resource-Efficient Lipreading with Efficientnetv2 and Transformers
Multistream neural architectures for cued-speech recognition using a pre-trained visual feature extractor and constrained CTC decoding
Multi-modality Associative Bridging through Memory: Speech Sound Recollected from Face Video
Distinguishing Homophenes Using Multi-Head Visual-Audio Memory for Lip Reading
Self-supervised Transformer for Deepfake Detection
Visual Speech Recognition for Multiple Languages in the Wild
Leveraging Unimodal Self-Supervised Learning for Multimodal Audio-Visual Speech Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.