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A Neural Pairwise Ranking Model for Readability Assessment ...
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SMDT: Selective Memory-Augmented Neural Document Translation ...
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CausalKG: Causal Knowledge Graph Explainability using interventional and counterfactual reasoning ...
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Learn from Structural Scope: Improving Aspect-Level Sentiment Analysis with Hybrid Graph Convolutional Networks ...
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Learning the Ordering of Coordinate Compounds and Elaborate Expressions in Hmong, Lahu, and Chinese ...
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Deep Neural Convolutive Matrix Factorization for Articulatory Representation Decomposition ...
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Modeling Intensification for Sign Language Generation: A Computational Approach ...
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A Transformer-Based Contrastive Learning Approach for Few-Shot Sign Language Recognition ...
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Open Source HamNoSys Parser for Multilingual Sign Language Encoding ...
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A Comprehensive Review of Sign Language Recognition: Different Types, Modalities, and Datasets ...
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Sign Language Video Retrieval with Free-Form Textual Queries ...
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Sign Language Recognition System using TensorFlow Object Detection API ...
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Abstract:
Communication is defined as the act of sharing or exchanging information, ideas or feelings. To establish communication between two people, both of them are required to have knowledge and understanding of a common language. But in the case of deaf and dumb people, the means of communication are different. Deaf is the inability to hear and dumb is the inability to speak. They communicate using sign language among themselves and with normal people but normal people do not take seriously the importance of sign language. Not everyone possesses the knowledge and understanding of sign language which makes communication difficult between a normal person and a deaf and dumb person. To overcome this barrier, one can build a model based on machine learning. A model can be trained to recognize different gestures of sign language and translate them into English. This will help a lot of people in communicating and conversing with deaf and dumb people. The existing Indian Sing Language Recognition systems are designed ... : 14 pages, 5 figures, ANTIC 2021 ...
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Keyword:
Artificial Intelligence cs.AI; Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences; Machine Learning cs.LG; Multimedia cs.MM
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URL: https://dx.doi.org/10.48550/arxiv.2201.01486 https://arxiv.org/abs/2201.01486
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pNLP-Mixer: an Efficient all-MLP Architecture for Language ...
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Listening to Affected Communities to Define Extreme Speech: Dataset and Experiments ...
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Cross-Lingual Text-to-Speech Using Multi-Task Learning and Speaker Classifier Joint Training ...
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Focus on the Target's Vocabulary: Masked Label Smoothing for Machine Translation ...
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Sememe Prediction for BabelNet Synsets using Multilingual and Multimodal Information ...
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Multilingual Mix: Example Interpolation Improves Multilingual Neural Machine Translation ...
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