Data

Zelda Smart Home Prototype

The University of Queensland
Dr Jessica Korte (Aggregated by) Dr Jessica Korte (Aggregated by) Ms Adele Greedy-Vogel (Aggregated by) Ms Julie Lyons (Aggregated by) Ms Maria Zelenskaya (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/bc096fa&rft.title=Zelda Smart Home Prototype&rft.identifier=RDM ID: 3327246f-08dc-4eab-ae05-ba8cb467085f&rft.publisher=The University of Queensland&rft.description=This is the avatar and animation set created for the Auslan Communication Technologies Pipeline project. It is the core of the demo presented in Zelenskaya et al., 2023, however the virtual smart home included in the demo was removed in this prototype, as it was created using third party assets. This prototype contains: 1) An Unreal Engine project with the Zelda avatar as it was used in the demo; 2) Models and scripts for recognising emblematic gestures inspired by Auslan signs, disambiguating from context, assembling a command, executing the command, and generating an appropriate response from the avatar; 3) Instructions on setting up SplitCam to use a single webcam as input in two locations; 4) Instructions on connecting MediaPipe to Unreal Engine to run the prototype; 5) The required version of Python (3.9); 6) The Unreal Engine project we used to record Auslan signs through motion capture; and 7) Several backup versions of the avatar, and tracking, and HTTP communication, from previous iterations of the prototype.&rft.creator=Dr Jessica Korte&rft.creator=Dr Jessica Korte&rft.creator=Ms Adele Greedy-Vogel&rft.creator=Ms Julie Lyons&rft.creator=Ms Maria Zelenskaya&rft.creator=Ms Maria Zelenskaya&rft.date=2024&rft_rights= https://guides.library.uq.edu.au/deposit-your-data/license-reuse-data-agreement&rft_subject=eng&rft_subject=Natural language processing&rft_subject=Artificial intelligence&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft_subject=Deep learning&rft_subject=Machine learning&rft_subject=Language studies not elsewhere classified&rft_subject=Language studies&rft_subject=LANGUAGE, COMMUNICATION AND CULTURE&rft.type=dataset&rft.language=English Access the data
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[email protected]
School of Electrical Engineering and Computer Science

Full description

This is the avatar and animation set created for the Auslan Communication Technologies Pipeline project. It is the core of the demo presented in Zelenskaya et al., 2023, however the virtual smart home included in the demo was removed in this prototype, as it was created using third party assets. This prototype contains: 1) An Unreal Engine project with the Zelda avatar as it was used in the demo; 2) Models and scripts for recognising emblematic gestures inspired by Auslan signs, disambiguating from context, assembling a command, executing the command, and generating an appropriate response from the avatar; 3) Instructions on setting up SplitCam to use a single webcam as input in two locations; 4) Instructions on connecting MediaPipe to Unreal Engine to run the prototype; 5) The required version of Python (3.9); 6) The Unreal Engine project we used to record Auslan signs through motion capture; and 7) Several backup versions of the avatar, and tracking, and HTTP communication, from previous iterations of the prototype.

Issued: 2024

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Subjects
Artificial Intelligence | Deep Learning | Information and Computing Sciences | Language, Communication and Culture | Language Studies | Language Studies Not Elsewhere Classified | Machine Learning | Natural Language Processing | eng |

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