Name
Abstract | ||
|---|---|---|
The usability and health of a person's voice has dire impact on the person's quality of life. Pathological issues that may exist on a person's voice often cannot be detected by a regular listener. Medical attention from a professional may be necessary to detect vocal pathologies. Analysis of the patients complaints and a perceptual evaluation performed by a doctor is one of the most common ways to diagnose a vocal condition. This method can be invasive, time consuming and expensive. Features of the voice can be extracted and utilized in a computer environment to make the same diagnosis which may increase the speed and accuracy of the diagnosis and decrease the cost. In this paper, a cloud application which collects vocal data in a database is proposed. With data mining and machine learning methods, a new tool has been developed to detect and diagnose vocal anomalies in patients. The effectiveness of the suggested platform has been demonstrated with a pathological detection and recognition application running in the server. |
Year | Venue | Keywords |
|---|---|---|
2017 | Signal Processing and Communications Applications Conference | Pathologic voice detection,voice treatment,voice cloud,machine learning,big data |
Field | DocType | ISSN |
Computer science,Usability,Support vector machine,Speech recognition,Feature extraction,Perception,Cloud computing | Conference | 2165-0608 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hasan Can Aydan | 1 | 0 | 0.68 |
| Meral Korkmaz | 2 | 0 | 0.34 |
| Beyza Cizmeci | 3 | 0 | 0.34 |
| Ismail Kocak | 4 | 1 | 1.37 |
| Nilufer Egrican | 5 | 0 | 0.34 |
| Gökhan Ince | 6 | 13 | 10.03 |