2021 IEEE International Conference on Acoustics, Speech and Signal Processing
6-11 June 2021 • Toronto, Ontario, Canada
Extracting Knowledge from Information
| Paper ID | SPE-46.6 | ||
| Paper Title | THE IN-THE-WILD SPEECH MEDICAL CORPUS | ||
| Authors | Joana Correia, Carnegie Mellon University / U. Lisbon / INESC, United States; Francisco Teixeira, Catarina Botelho, Isabel Trancoso, U. Lisbon / INESC, Portugal; Bhiksha Raj, Carnegie Mellon University, United States | ||
| Session | SPE-46: Corpora and Other Resources | ||
| Location | Gather.Town | ||
| Session Time: | Thursday, 10 June, 16:30 - 17:15 | ||
| Presentation Time: | Thursday, 10 June, 16:30 - 17:15 | ||
| Presentation | Poster | ||
| Topic | Human Language Technology: [HLT-LRES] Language Resources and Systems | ||
| IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
| Abstract | Automatic detection of speech affecting (SA) diseases has received significant attention, particularly in clinical scenarios. However, the same task in in-the-wild conditions is often neglected, in part, due to the lack of appropriate datasets. In this work, we present the in-the-Wild Speech Medical (WSM) Corpus, a collection of in-the-wild videos, featuring subjects potentially affected by a SA disease - specifically, depression or Parkinson's disease. The WSM Corpus contains a total 928 videos, and over 131 hours of speech. Each video is accompanied by a crowdsourced annotation for perceived age/gender, and self-reported health status of the speaker. The WSM Corpus is balanced over all the labels. In this work we present a detailed description of the collection, and annotation processes of the WSM corpus. Furthermore, we present present several baseline systems for the detection of SA diseases using speech alone, thus motivating the use of this type of in-the-wild data in paralinguistic audiovisual tasks. | ||