ASL Translation Object Detection Dataset and Pre-Trained Model by Prima Vista Supreme

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Explore Dataset

Here are a few use cases for this project:

Education: This model can be used as a learning tool for individuals seeking to learn American Sign Language (ASL). It can provide real-time feedback on their sign language gestures based on its knowledge of the correct gestures for each letter.
Communication Aid: For those who are hearing-impaired or speech-impaired, the model can serve as a communication tool, converting ASL signs into text.
Telecommunication Services: Video chat or telecommunication platforms can integrate this model to provide live subtitles for individuals using ASL during calls, enhancing accessibility.
Public Services: Institutions such as libraries, hospitals, or customer service departments can use this model to better communicate with ASL-using customers, improving customer experience and inclusivity.
Entertainment: Game developers can make their games more inclusive and interactive by integrating this model, thus allowing users to control gameplay using ASL signs.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            asl-translation-qylpl_dataset,
                            title = { ASL Translation Dataset },
                            type = { Open Source Dataset },
                            author = { Prima Vista Supreme },
                            howpublished = { \url{ https://universe.roboflow.com/prima-vista-supreme/asl-translation-qylpl } },
                            url = { https://universe.roboflow.com/prima-vista-supreme/asl-translation-qylpl },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jul },
                            note = { visited on 2024-04-27 },
                            }