Services on Demand
Journal
Article
Indicators
- Cited by SciELO
- Access statistics
Related links
- Cited by Google
- Similars in SciELO
- Similars in Google
Share
DYNA
Print version ISSN 0012-7353
Abstract
WILCHES-CORTINA, Juan Ricardo; CARDONA-PENA, Jairo Alberto and TELLO-PORTILLO, Juan Pablo. A VoIP call classifier for carrier grade based on Support Vector Machines. Dyna rev.fac.nac.minas [online]. 2017, vol.84, n.202, pp.75-83. ISSN 0012-7353. https://doi.org/10.15446/dyna.v84n202.60975.
Currently, VoIP company technicians conduct tests to classify call quality as good or bad. Even though, there are automatic platforms that make test VoIP calls to classify them, they do not perform audio processing to detect False Answer Supervision (FAS), which is a common and undesirable feature of VoIP calls. In this paper, a Vector Support Machine (SVM) along with several functions used in voice recognition were implemented to emulate the human decision procedure (the task of audio classification and analysis performed by technicians). The experiments were based on the comparison between the results obtained from the current classification methods and those derived from the SVM. A 10-fold cross-validation was used to evaluate the system performance. The tests results from the proposed methodology show a better percentage of successful classification compared to a selected automatic platform called CheckMyRoutes.
Keywords : Audio analysis; pattern recognition; SVM; VoIP..