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Sistem za samodejno razpoznavanje varnostno sumljivih zvokov
ID SABADIN, JERNEJ (Author), ID Dobrišek, Simon (Mentor) More about this mentor... This link opens in a new window

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Abstract
Zasnujte in izvedite preizkus izbranih metod samodejnega razpoznavanja varnostno sumljivih zvokov. Za izvedbo metod strojnega učenja izbranih modelov razpoznavalnikov in ugotavljanje njihove natančnosti pridobite zbirko posnetkov varnostno sumljivih zvokov in drugih običajnih zvokov v okolju, ki jo sestavite iz razpoložljivih javno dostopnih tovrstnih posnetkov. Natančnost samodejnega razpoznavanja varnostno sumljivih zvokov ovrednotite z izbranimi merami, ki se uporabljajo na tem področju, ter primerno razdelitvijo uporabljene zbirke zvočnih posnetkov na množico učnih in testnih posnetkov.

Language:Slovenian
Keywords:razpoznavanje sumljivih zvokov, zbirka, kratkočasovne značilke, nevronsko omrežje, dinamično ukrivljanje časovne osi, metoda k-najbližjih sosedov, podporni vektorji.
Work type:Bachelor thesis/paper
Organization:FE - Faculty of Electrical Engineering
Year:2022
PID:20.500.12556/RUL-138144 This link opens in a new window
COBISS.SI-ID:115075075 This link opens in a new window
Publication date in RUL:12.07.2022
Views:1364
Downloads:116
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Secondary language

Language:English
Title:A system for automatic suspicious sound detection
Abstract:
Design and conduct a test of selected methods of automatic recognition of security-suspicious sounds. To implement machine learning methods of selected recognizer models and determine their accuracy, obtain a collection of recordings of security-suspicious sounds and other common sounds in the environment, which you compile from publicly available recordings of this type. You evaluate the accuracy of the automatic recognition of security-suspicious sounds with the selected measures used in this field, as well as the appropriate division of the used collection of audio recordings into a set of training and test recordings.

Keywords:detection of security suspicious sounds, data collection, short-time characteristic of sounds, neural network, Dynamic Time Warping wrapping, k-nearest neighbors algorithm, Supported Vector Machine.

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