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Chapter

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Title

Classification of emergency phone conversations with artificial neural network

Authors

[ 1 ] Instytut Automatyki i Robotyki, Wydział Informatyki, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.2] Automation, electronics and electrical engineering

Year of publication

2017

Chapter type

chapter in monograph / paper

Publication language

english

Keywords
EN
  • emergency telephone
  • artificial neural network
  • speaker classification
  • event classification
  • metadata
Abstract

EN This paper presents a series of experiments on the classification of emergency phone conversation records using artificial neural networks (ANNs). Input data which were processed by ANNs were the features of callers and events taken from emergency phone calls. The authors analyzed four variants of classification: the groups of callers which have specified features, the groups of events which have specified features, selected callers, and selected events. Then the efficiency of classification by the ANN (artificial neural network) with various sets of features was compared. Results show that ANNs can properly classify precisely defined callers or events, from e.g. so called `black-list' of callers.

Date of online publication

07.12.2017

Pages (from - to)

343 - 348

DOI

10.23919/SPA.2017.8166890

URL

https://ieeexplore.ieee.org/document/8166890

Book

SPA 2017 Signal Processing: Algorithms, Architectures, Arrangements, and Applications, Poznan, 22-24 September 2017 : conference proceedings

Presented on

21st IEEE Conference Signal Processing - Algorithms, Architectures, Arrangements, and Applications, SPA 2017, 20-22.09.2017, Poznan, Poland

Ministry points / chapter

20

Publication indexed in

WoS (15)

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