Speech technologies are more important every day to assist people with speech disorders. They can help to increase their quality of life or help clinicians to make a diagnosis. In this paper a new methodology based on a total variability subspace modelled by factor analysis is proposed to assess the intelligibility of people with dysarthria. The acoustic information of each recording is efficiently compressed and a Pearson correlation of 0.91 between the vectors in this subspace (iVectors) and the intelligibility is obtained. As acoustic information only perceptual linear prediction features are used. The experiments are conducted on Universal Access Speech database. Also a new error metric to overcome the subjectivity in the intelligibility labels is proposed.
Bibliographic reference. Martínez, David / Green, Phil D. / Christensen, H. (2013): "Dysarthria intelligibility assessment in a factor analysis total variability space", In INTERSPEECH-2013, 2133-2137.