Audio–visual speech recognition based on regulated transformer and spatio–temporal fusion strategy for driver assistive systems-Reference-Cited by-同舟云学术

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Audio–visual speech recognition based on regulated transformer and spatio–temporal fusion strategy for driver assistive systems

Published:2024-10 Issue: Volume:252 Page:124159
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Ryumin Dmitry^ORCID,Axyonov Alexandr^ORCID,Ryumina Elena^ORCID,Ivanko Denis^ORCID,Kashevnik Alexey^ORCID,Karpov Alexey^ORCID

Funder

Analytical Center for the Government of the Russian Federation

Publisher

Elsevier BV

Reference94 articles.

1. Contextual deep learning-based audio-visual switching for speech enhancement in real-world environments;Adeel;Information Fusion,2020

2. Deep audio-visual speech recognition;Afouras;IEEE Transactions on Pattern Analysis and Machine Intelligence,2018

3. LRS3-TED: A large-scale dataset for visual speech recognition;Afouras,2018

4. Voice interfaced vehicle user help;Alvarez,2010

5. MuAViC: A multilingual audio-visual corpus for robust speech recognition and robust speech-to-text translation;Anwar,2023

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1. AVaTER: Fusing Audio, Visual, and Textual Modalities Using Cross-Modal Attention for Emotion Recognition;Sensors;2024-09-10

2. Hybridization of Acoustic and Visual Features of Polish Sibilants Produced by Children for Computer Speech Diagnosis;Sensors;2024-08-19

3. Enhancing Air Traffic Control Communication Systems with Integrated Automatic Speech Recognition: Models, Applications and Performance Evaluation;Sensors;2024-07-20

4. Nonlinear Regularization Decoding Method for Speech Recognition;Sensors;2024-06-14

5. The Application of Intelligent Speech Recognition in the Teaching of Spoken English in Colleges and Universities;Applied Mathematics and Nonlinear Sciences;2024-01-01

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