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Audio Visual Speech Recognition On Lrs3 Ted

Métriques

Word Error Rate (WER)

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Word Error Rate (WER)	Paper Title	Repository
EG-seq2seq	6.8	Discriminative Multi-modality Speech Recognition	-
DistillAV	1.3	Audio-Visual Representation Learning via Knowledge Distillation from Speech Foundation Models	-
TM-seq2seq	7.2	Deep Audio-Visual Speech Recognition	-
RNN-T	4.5	Recurrent Neural Network Transducer for Audio-Visual Speech Recognition	-
Hyb-Conformer	2.3	End-to-end Audio-visual Speech Recognition with Conformers	-
AV-HuBERT Large	1.4	Robust Self-Supervised Audio-Visual Speech Recognition	-
Llama-AVSR	0.77	Large Language Models are Strong Audio-Visual Speech Recognition Learners	-
CTC/Attention	0.9	Auto-AVSR: Audio-Visual Speech Recognition with Automatic Labels	-
Whisper-Flamingo	0.76	Whisper-Flamingo: Integrating Visual Features into Whisper for Audio-Visual Speech Recognition and Translation	-
RAVEn Large	1.4	Jointly Learning Visual and Auditory Speech Representations from Raw Data	-
Zero-AVSR	1.5	Zero-AVSR: Zero-Shot Audio-Visual Speech Recognition with LLMs by Learning Language-Agnostic Speech Representations	-
MMS-LLaMA	0.74	MMS-LLaMA: Efficient LLM-based Audio-Visual Speech Recognition with Minimal Multimodal Speech Tokens	-

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Audio Visual Speech Recognition On Lrs3 Ted | SOTA | HyperAI