speech31/easycall-dysarthria

EasyCall

The EasyCall corpus is a database of command speech recorded from healthy individuals and dysarthric patients.

Dataset Details

Dataset Description

This dataset has been collected through a collaboration between the Italian Institute of Technology (IIT), the University of Ferrara and the Sant'Anna Hospital of Ferrara, and it aims at providing a new resource for future developments of ASR-based assistive technologies. In particular, it may be exploited to develop a voice-controlled contact application for commercial smartphones, and improve dysarthric patients' ability to communicate with their family and caregivers.

• Curated by: Rosanna Turrisi, Arianna Braccia, Marco Emanuele, Simone Giulietti, Luciano Fadiga, Mariachiara Sensi, Leonardo Badino.
• License: CC BY-NC

Dataset Sources

• Repository: http://neurolab.unife.it/easycallcorpus/

Dataset Structure

It currently consists of 16683 audio recordings from 21 healthy and 26 dysarthric speakers. For each speech-impaired individual, dysarthria has been assessed by a neurologist through the Therapy Outcome Measure. The recordings focus on a small vocabulary, including basic smartphone commands, such as “open contacts”, “start call”, “end call”. Specifically, these commands are the result of a survey administered to patients that evaluates which commands are more likely to be employed by dysarthric individuals to use a speech command-based contact application.
In addition, the dataset includes a list of non-commands (i.e., words near/inside commands or phonetically close to commands) that can be leveraged to build a more robust ASR system.

Citation

If you use this dataset, please cite the following publication: BibTeX: @inproceedings{turrisi21_interspeech, title = {EasyCall Corpus: A Dysarthric Speech Dataset}, author = {Rosanna Turrisi and Arianna Braccia and Marco Emanuele and Simone Giulietti and Maura Pugliatti and Mariachiara Sensi and Luciano Fadiga and Leonardo Badino}, year = {2021}, booktitle = {Interspeech 2021}, pages = {41--45}, doi = {10.21437/Interspeech.2021-549}, issn = {2958-1796}, }