We will present the following paper at the Language Resources and Evaluation Conference (LREC 2018):
 | Arif Khan; Ingmar Steiner; Yusuke Sugano; Andreas Bulling; Ross Macdonald A Multimodal Corpus of Expert Gaze and Behavior during Phonetic Segmentation Tasks Inproceedings Proc. Language Resources and Evaluation Conference (LREC), 2018. Abstract | Links | BibTeX @inproceedings{khan18_lrec,
title = {A Multimodal Corpus of Expert Gaze and Behavior during Phonetic Segmentation Tasks},
author = {Arif Khan and Ingmar Steiner and Yusuke Sugano and Andreas Bulling and Ross Macdonald},
url = {https://perceptual.mpi-inf.mpg.de/files/2018/05/khan18_lrec.pdf
https://git.io/eyeseg-data},
year = {2018},
date = {2018-01-01},
booktitle = {Proc. Language Resources and Evaluation Conference (LREC)},
abstract = {Phonetic segmentation is the process of splitting speech into distinct phonetic units. Human experts routinely perform this task manually by analyzing auditory and visual cues using analysis software, which is an extremely time-consuming process. Methods exist for automatic segmentation, but these are not always accurate enough. In order to improve automatic segmentation, we need to model it as close to the manual segmentation as possible. This corpus is an effort to capture the human segmentation behavior by recording experts performing a segmentation task. We believe that this data will enable us to highlight the important aspects of manual segmentation, which can be used in automatic segmentation to improve its accuracy.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Phonetic segmentation is the process of splitting speech into distinct phonetic units. Human experts routinely perform this task manually by analyzing auditory and visual cues using analysis software, which is an extremely time-consuming process. Methods exist for automatic segmentation, but these are not always accurate enough. In order to improve automatic segmentation, we need to model it as close to the manual segmentation as possible. This corpus is an effort to capture the human segmentation behavior by recording experts performing a segmentation task. We believe that this data will enable us to highlight the important aspects of manual segmentation, which can be used in automatic segmentation to improve its accuracy. |