by Meier, Moritz, Mason, Celeste, Putze, Felix and Schultz, Tanja
Abstract:
We describe our efforts to compare data collection methods using two think-aloud protocols in preparation to be used as a basis for automatic structuring and labeling of a large database of high-dimensional human activities data into a valuable resource for research in cognitive robotics. The envisioned dataset, currently in development, will contain synchronously recorded multimodal data, including audio, video, and biosignals (eye-tracking, motion-tracking, muscle and brain activity) from about 100 participants performing everyday activities while describing their task through use of think-aloud protocols. This paper provides details of our pilot recordings in the well-established and scalable "table setting scenario," describes the concurrent and retrospective think-aloud protocols used, the methods used to analyze them, and compares their potential impact on the data collected as well as the automatic data segmentation and structuring process.
Reference:
Meier, Moritz, Mason, Celeste, Putze, Felix and Schultz, Tanja, "Comparative Analysis of Think-aloud Methods for Everyday Activities in the Context of Cognitive Robotics", In 20th Annual Conference of the International Speech Communication Association, Graz, Austria, 2019.
Bibtex Entry:
@inproceedings{meier_interspeech_2019,
note={Interspeech 2019},
title={Comparative Analysis of Think-aloud Methods for Everyday Activities in the Context of Cognitive Robotics},
year={2019},
month={October},
booktitle={20th Annual Conference of the International Speech Communication Association},
address={Graz, Austria},
author={Meier, Moritz and Mason, Celeste and Putze, Felix and Schultz, Tanja},
url={https://www.csl.uni-bremen.de/cms/images/documents/publications/meier_interspeech_2019.pdf},
abstract={We describe our efforts to compare data collection methods using two think-aloud protocols in preparation to be used as a basis for automatic structuring and labeling of a large database of high-dimensional human activities data into a valuable resource for research in cognitive robotics. The envisioned dataset, currently in development, will contain synchronously recorded multimodal data, including audio, video, and biosignals (eye-tracking, motion-tracking, muscle and brain activity) from about 100 participants performing everyday activities while describing their task through use of think-aloud protocols. This paper provides details of our pilot recordings in the well-established and scalable ``table setting scenario," describes the concurrent and retrospective think-aloud protocols used, the methods used to analyze them, and compares their potential impact on the data collected as well as the automatic data segmentation and structuring process.},
keywords={easecrc_human_cognition, easecrc_cognitive_arch_systems},
}