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Extraction of specific data from a sound sample by removing additional distortion

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Correct identity recognition based on a voice sample must deal with many problems such as too big or small distance from the microphone, noise or abnormal voice. Hoarseness, coughing or even stuttering can also be encountered as disturbance of the voice. Research on new aspects of intelligent processing for voice brings possibilities to use intelligent methods to increase efficiency in processing and quality of record. In this paper, a spectrogram analysis for the detection of specific data and remove these distortions in the sample is presented. The proposed solution has been tested and discussed for real use in identity verification systems.

Original languageEnglish
Title of host publicationProceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017
EditorsMaria Ganzha, Leszek Maciaszek, Marcin Paprzycki
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages353-356
Number of pages4
ISBN (Electronic)9788394625375
DOIs
Publication statusPublished - 10 Nov 2017
Event2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017 - Prague, Czech Republic
Duration: 3 Sept 20176 Sept 2017

Publication series

NameProceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017

Conference

Conference2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017
Country/TerritoryCzech Republic
CityPrague
Period3/09/176/09/17

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems

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