A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is
This paper looks in more detail at the Interspeech 2019 computational paralinguistics challenge on the prediction of sleepiness ratings from speech. In this challenge, teams were asked to train a regression model to predict sleepiness from samples of the Düsseldorf Sleepy Language Corpus (DSLC). This challenge was notable because the performance of all entrants was uniformly poor, with even the winning system only achieving a correlation of r=0.37. We look at whether the task itself isdoi:10.21437/interspeech.2020-1601 dblp:conf/interspeech/HuckvaleBI20 fatcat:wmusbd4yljbdbg2jj3bxvx5h6m