Name
Abstract | ||
|---|---|---|
The general aim of this work is to learn a unique statistical signature for the state of a particular speech pathology. We pose this as a speaker identification problem for dysarthric individuals. To that end, we propose a novel algorithm for feature selection that aims to minimize the effects of speaker-specific features (e.g., fundamental frequency) and maximize the effects of pathology-specific features (e.g., vocal tract distortions and speech rhythm). We derive a cost function for optimizing feature selection that simultaneously trades off between these two competing criteria. Furthermore, we develop an efficient algorithm that optimizes this cost function and test the algorithm on a set of 34 dysarthric and 13 healthy speakers. Results show that the proposed method yields a set of features related to the speech disorder and not an individual's speaking style. When compared to other feature-selection algorithms, the proposed approach results in an improvement in a disorder fingerprinting task by selecting features that are specific to the disorder. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6639133 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
feature extraction,medical disorders,medical signal processing,speaker recognition,speech intelligibility,speech processing,disorder-specific feature selection,dysarthric individuals,fundamental frequency,pathology-specific features,speaker identification,speaker-specific features,speech disorder,speech pathology fingerprinting,speech rhythm,unique statistical signature,vocal tract distortions,dysarthria,feature selection,machine learning,speech pathology | Speech processing,Pattern recognition,Feature selection,Computer science,Feature extraction,Speech recognition,Speaker recognition,Speech disorder,Artificial intelligence,Dysarthria,Vocal tract,Intelligibility (communication) | Conference |
ISSN | Citations | PageRank |
1520-6149 | 1 | 0.37 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Visar Berisha | 1 | 76 | 22.38 |
| Steven Sandoval | 2 | 24 | 4.53 |
| Utianski, R. | 3 | 1 | 0.37 |
| Liss, J. | 4 | 1 | 0.37 |