Towards AI-enhanced ballet learning
Since its codified genesis in the 18th century, ballet training has largely been unchanged: it relies on the word of mouth expertise passed down generation to generation and in tools that do not adequately support both dancers and teachers. Moreover, top-tier training is only found in a few locations around the world and comes at an exceptional price. In this context, artificial intelligence (AI)-based video tools might represent an affordable and non-invasive alternative: it would allow dancers and teachers to self-assess as well as enable skilled dance teachers to connect with a wider audience. In my research, I study how to design and evaluate AI-based tools to improve ballet performance for dancers and teachers.
© Copyright 2019 Proceedings of the 6th International Conference on Movement and Computing. Published by ACM. All rights reserved.
| Subjects: | |
|---|---|
| Notations: | technical and natural sciences technical sports |
| Tagging: | künstliche Intelligenz |
| Published in: | Proceedings of the 6th International Conference on Movement and Computing |
| Language: | English |
| Published: |
New York
ACM
2019
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| Series: | MOCO '19 |
| Online Access: | https://doi.org/10.1145/3347122.3371380 |
| Pages: | Article 34 |
| Document types: | article |
| Level: | advanced |