SOTAVerified

Lip Reading

Lip Reading is a task to infer the speech content in a video by using only the visual information, especially the lip movements. It has many crucial applications in practice, such as assisting audio-based speech recognition, biometric authentication and aiding hearing-impaired people.

Source: Mutual Information Maximization for Effective Lip Reading

Papers

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Showing 1–25 of 153 papers

TitleStatusHype
GeneFace: Generalized and High-Fidelity Audio-Driven 3D Talking Face SynthesisCode4
Where Visual Speech Meets Language: VSP-LLM Framework for Efficient and Context-Aware Visual Speech ProcessingCode3
Learning Audio-Visual Speech Representation by Masked Multimodal Cluster PredictionCode2
Seeing What You Said: Talking Face Generation Guided by a Lip Reading ExpertCode2
Training Strategies for Improved Lip-readingCode2
OpenSR: Open-Modality Speech Recognition via Maintaining Multi-Modality AlignmentCode1
Mutual Information Maximization for Effective Lip ReadingCode1
Personalized Lip Reading: Adapting to Your Unique Lip Movements with Vision and LanguageCode1
Lipreading using Temporal Convolutional NetworksCode1
Learning Individual Speaking Styles for Accurate Lip to Speech SynthesisCode1
MixSpeech: Cross-Modality Self-Learning with Audio-Visual Stream Mixup for Visual Speech Translation and RecognitionCode1
Multi-modality Associative Bridging through Memory: Speech Sound Recollected from Face VideoCode1
Neural Text to Articulate Talk: Deep Text to Audiovisual Speech Synthesis achieving both Auditory and Photo-realismCode1
OLKAVS: An Open Large-Scale Korean Audio-Visual Speech DatasetCode1
Lip-reading with Densely Connected Temporal Convolutional NetworksCode1
End-to-end Audio-visual Speech Recognition with ConformersCode1
Do VSR Models Generalize Beyond LRS3?Code1
End-to-End Speech-Driven Facial Animation with Temporal GANsCode1
Learn an Effective Lip Reading Model without PainsCode1
Deformation Flow Based Two-Stream Network for Lip ReadingCode1
Can We Read Speech Beyond the Lips? Rethinking RoI Selection for Deep Visual Speech RecognitionCode1
Leveraging Unimodal Self-Supervised Learning for Multimodal Audio-Visual Speech RecognitionCode1
Audio-Visual Efficient Conformer for Robust Speech RecognitionCode1
Contrastive Learning of Global-Local Video RepresentationsCode1
Deep Audio-Visual Speech RecognitionCode1
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All datasetsGRID corpus (mixed-speech)LRWTCD-TIMIT corpus (mixed-speech)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Lip2WavWER14.08—Unverified
#ModelMetricClaimedVerifiedStatus
1Lip2WavWER34.2—Unverified
#ModelMetricClaimedVerifiedStatus
1Lip2WavWER31.26—Unverified