A VoIP call classifier for carrier grade based on Support Vector Machines

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 o...

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Autores:: Wilches-Cortina, Juan Ricardo
Cardona-Peña, Jairo Alberto
Tello-Portillo, Juan Pablo

Tipo de recurso:: Article of journal

Fecha de publicación:: 2017

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

Description
Summary:	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.

A VoIP call classifier for carrier grade based on Support Vector Machines

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