Paper Info
Title
Automatic Prediction Of Speech Evaluation Metrics For Dysarthric Speech
Abstract
During the last decades, automatic speech processing systems witnessed an important progress and achieved remarkable reliability. As a result, such technologies have been exploited in new areas and applications including medical practice. In disordered speech evaluation context, perceptual evaluation is still the most common method used in clinical practice for the diagnosing and the following of the condition progression of patients despite its well documented limits (such as subjectivity).In this paper, we propose an automatic approach for the prediction of dysarthric speech evaluation metrics (intelligibility. severity, articulation impairment) based on the representation of the speech acoustics in the total variability subspace based on the i-vectors paradigm. The proposed approach, evaluated on 129 French dysarthric speakers from the DesPhoAPady and VML databases, is proven to be efficient for the modeling of patient's production and capable of detecting the evolution of speech quality. Also, low RMSE and high correlation measures are obtained between automatically predicted metrics and perceptual evaluations.
Year
DOI
Venue
2017
10.21437/Interspeech.2017-1363
18TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2017), VOLS 1-6: SITUATED INTERACTION
Keywords
Field
DocType
Dysarthria, speech disorders, automatic speech processing, i-vectors, speech intelligibility
Dysarthric speech,Automatic speech,Computer science,Speech quality,Natural language processing,Artificial intelligence,Intelligibility (communication),Pattern recognition,Subspace topology,Speech recognition,Correlation,Perception,Speech Acoustics
Conference
ISSN
Citations 
PageRank 
2308-457X
3
0.44
References 
Authors
9
4
Name
Order
Citations
PageRank
Imed Laaridh1133.71
Waad Ben Kheder2195.05
corinne fredouille353744.53
Christine Meunier41910.61