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AI for Good-Innovate for Impact



                      Use Case – 11: Libras Project






                      Country: Brazil 

                      Organization: Lenovo 

                      Contact person: Hildebrando Lima, hlima1@ lenovo .com  


                      11�1� Use case summary table

                       Domain                   Accessibility

                       Problem to be addressed   Communication with the hearing impaired 
                       Key aspects of the solution  Sign language (Libras) to text (Brazilian language), (text to sign
                                                language) using avatars
                       Technology keywords      Classifier Model、Digital Avatar

                       Data availability        Private 

                       Metadata (type of data)   Articulation points, Movements, Vectors
                       Model Training and fine   Classifier
                       tuning 
                       Testbeds or pilot deploy-  PC support using sign language, via Lenovo portal
                       ments 


                      11�2� Use case description



                      11�2�1� Description 

                      Introduction: Communication barriers for the hearing-impaired pose significant challenges in
                      daily interactions, hindering their ability to engage effectively with others. Sign language serves
                      as a primary means of communication for individuals using Libras (Brazilian Sign Language),
                      but the lack of widespread understanding can lead to misunderstandings and isolation. This
                      use case addresses these challenges by leveraging AI-driven technology to facilitate seamless
                      communication between individuals using sign language and those using spoken language.


                      Solution Overview: The solution focuses on developing a robust translation tool that translates
                      sign language (Libras) into Brazilian text and audio, and vice versa, using digital avatars[2].
                      Using a classifier model and digital avatars, the solution accurately captures and translates
                      sign language gestures into written and spoken language, bridging the communication gap
                      between the hearing impaired and the broader community. Access to private data, including
                      vectors from individuals using Libras, enables the training and fine-tuning of the classifier
                      model to ensure accurate translation. GPU resources are utilized for efficient processing,
                      while metadata such as articulation points and movements enhance translation accuracy. Pilot
                      deployments, including PC support via the Lenovo portal, validate the solution's effectiveness
                      in real-world scenarios.




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