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Open Access
Natural Language Programming: How Laypersons Teach New Functions to Robots
- Citation Author(s):
- Submitted by:
- Sebastian Weigelt
- Last updated:
- Tue, 10/15/2019 - 11:29
- DOI:
- 10.21227/zecn-6c61
- Data Format:
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Abstract
Even though intelligent systems such as Siri or Google Assistant are enjoyable (and useful) dialog partners, users can only access predefined functionality. Enabling end-users to extend the functionality of intelligent systems will be the next big thing. To promote research in this area we carried out an empirical study on how laypersons teach robots new functions by means of natural language instructions. The result is a labeled corpus consisting of 3168 submissions given by 870 subjects.
Instructions:
The Corpus consist of three datasets
- The raw dataset of submissions (without labels): raw_dataset.csv
- The labeled dataset: labeled_dataset.csv
- Personal data of the participants as provided by Prolific (Caution: Information are incomplete since registered members provide it voluntarily): personal_infomation_prolific.csv
Dataset Files
- The raw dataset of submissions (without labels) raw_dataset.csv (669.28 kB)
- The labeled dataset labeled_dataset.csv (1.95 MB)
- Personal data of the participants as provided by Prolific personal_infomation_prolific.csv (151.99 kB)
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