Automatised analysis of emergency calls using Natural Language Processing

Examensarbete för kandidatexamen

Please use this identifier to cite or link to this item:
Download file(s):
File Description SizeFormat 
244534.pdfFulltext12.95 MBAdobe PDFView/Open
Type: Examensarbete för kandidatexamen
Bachelor Thesis
Title: Automatised analysis of emergency calls using Natural Language Processing
Authors: Andersson, Emarin
Eriksson, Benjamin
Holmberg, Sofia
Hussain, Hossein
Jäberg, Lovisa
Thorsell, Erik
Abstract: The operators at SOS Alarm receives thousands of calls each day at the different emergency medical communication centres, owned by SOS Alarm, all over Sweden. A subset of these calls contain room for improvement and the operators could learn to improve from these calls. The work of finding – and analysing – these calls is however too tedious to be done by a human. This thesis presents four automatised solutions to this issue. The human factor is removed and the job of finding and analysing the calls is done by a computer. It is shown that it is possible to partly automatise the analysis, but the methods used have different strengths and weaknesses. Word frequency analysis is proven adequate at key word lookup. Similarity comparisons of various aspects of the calls are proven good at classifying calls, but less good at answering specific questions. Comparing parse trees seems promising, but the technology needs more work before it is ready to be used. The solutions presented show that it could be possible to automatise the analysis of the calls given that the right questions are asked and the results from these are used appropriately.
Keywords: Informations- och kommunikationsteknik;Data- och informationsvetenskap;Information & Communication Technology;Computer and Information Science
Issue Date: 2016
Publisher: Chalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)
Chalmers University of Technology / Department of Computer Science and Engineering (Chalmers)
Collection:Examensarbeten för kandidatexamen // Bachelor Theses

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.