Abstract
Natural Language Generation has been proved to be effective and efficient in constructing health behaviour change support systems. We are working on DrivingBeacon, a behaviour change support system that uses telematics data from mobile phone sensors to generate weekly data-to-text feedback reports to vehicle drivers. The system makes use of a wealth of information such as mobile phone use while driving, geo-information, speeding, rush hour driving to generate the feedback. We present results from a real-world evaluation where 8 drivers in UK used DrivingBeacon for 4 weeks. Results are promising but not conclusive.- Anthology ID:
- 2022.nlg4health-1.1
- Volume:
- Proceedings of the First Workshop on Natural Language Generation in Healthcare
- Month:
- July
- Year:
- 2022
- Address:
- Waterville, Maine, USA and virtual meeting
- Venue:
- NLG4Health
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1–8
- Language:
- URL:
- https://aclanthology.org/2022.nlg4health-1.1
- DOI:
- Cite (ACL):
- Jawwad Baig, Guanyi Chen, Chenghua Lin, and Ehud Reiter. 2022. DrivingBeacon: Driving Behaviour Change Support System Considering Mobile Use and Geo-information. In Proceedings of the First Workshop on Natural Language Generation in Healthcare, pages 1–8, Waterville, Maine, USA and virtual meeting. Association for Computational Linguistics.
- Cite (Informal):
- DrivingBeacon: Driving Behaviour Change Support System Considering Mobile Use and Geo-information (Baig et al., NLG4Health 2022)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2022.nlg4health-1.1.pdf