@inproceedings{1de395d0709b492eaf179969d962dc30,
title = "Extraction of key segments from day-long sound data",
abstract = "We propose a method to extract particular sound segments from the sound recorded during the course of a day in order to provide sound segments that can be used to facilitate memory. To extract important parts of the sound data, the proposed method utilizes human behavior based on a multisensing approach. To evaluate the performance of the proposed method, we conducted experiments using sound, acceleration, and global positioning system data collected by five participants for approximately two weeks. The experimental results are summarized as follows: (1) various sounds can be extracted by dividing a day into scenes using the acceleration data; (2) sound recorded in unusual places is preferable to sound recorded in usual places; and (3) speech is preferable to nonspeech sound.",
keywords = "Acceleration, GPS, Life-log, Multisensing, Sound, Syllable Count",
author = "Akinori Kasai and Sunao Hara and Masanobu Abe",
year = "2015",
month = jan,
day = "1",
doi = "10.1007/978-3-319-21380-4_105",
language = "English",
isbn = "9783319213798",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "620--626",
editor = "Constantine Stephanidis",
booktitle = "HCI International 2015 – Posters Extended Abstracts - International Conference, HCI International 2015, Proceedings",
note = "17th International Conference on Human Computer Interaction, HCI 2015 ; Conference date: 02-08-2015 Through 07-08-2015",
}