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DEEP LEARNING BASED SOUND EVENT RECOGNITION

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU135531" target="_blank" >RIV/00216305:26220/19:PU135531 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    DEEP LEARNING BASED SOUND EVENT RECOGNITION

  • Original language description

    The main paper deals with the analysis of the methods of processing and recognition of events in the audio signal and the implementation of the selected method in real use. Recognized events are gunshots placed in a background sound such as traffic noise, human voice, animal sounds and other forms of environmental sounds. For events classification and class recognition, the freely available machine learning framework TensorFlow is used.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20203 - Telecommunications

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 25th Conference STUDENT EEICT 2019

  • ISBN

    978-80-214-5735-5

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    1-4

  • Publisher name

    Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    Apr 25, 2019

  • Type of event by nationality

    CST - Celostátní akce

  • UT code for WoS article