  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.
