At Your Command! An Empirical Study on How Laypersons Teach Robots New Functions
Authors: Weigelt, Sebastian, Steurer, Vanessa and Tichy, Walter F.
Conference: IEEE 14th International Conference on Semantic Computing (ICSC), 2020
Paper (short)
Paper (long)
Slides
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. The analysis of the dataset revealed that many participants used certain wordings to express their wish to teach new functionality; two corresponding trigrams are among the most frequent. On the contrary, more than one third (36.93%) did not verbalize the teaching intent at all. We labeled the semantic constituents in the utterances: declaration (including the name of the function) and intermediate steps. The full corpus is publicly available: http://dx.doi.org/10.21227/zecn-6c61
Long Paper:
@inproceedings{weigeltyour2020,
title = {At Your {{Command}}! {{An Empirical Study}} on {{How LaypersonsTeach Robots New Functions}}},
booktitle = {{{arXiv}}:2009.06510 [Cs]},
author = {Weigelt, Sebastian and Steurer, Vanessa and Tichy, Walter F.},
year = {2020},
month = sep,
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. The analysis of the dataset revealed that many participants used certain wordings to express their wish to teach new functionality; two corresponding trigrams are among the most frequent. On the contrary, more than one third (36.93\%) did not verbalize the teaching intent at all. We labeled the semantic constituents in the utterances: declaration (including the name of the function) and intermediate steps. The full corpus is publicly available: http://dx.doi.org/10.21227/zecn-6c61},
archivePrefix = {arXiv},
eprint = {2009.06510},
eprinttype = {arxiv},
keywords = {Computer Science - Computation and Language,Computer Science - Information Retrieval},
primaryClass = {cs}
}