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Vgradni sistem za razpoznavanje govornih ukazov z uporabo modela konvolucijskega nevronskega omrežja
ID BREZNIK, MIHA (Author), ID Dobrišek, Simon (Mentor) More about this mentor... This link opens in a new window

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Abstract
Razpoznavanje besednih ukazov se dandanes uporablja v številnih procesih in napravah. Številne naprave so zgrajene z mikroprocesorji, ki imajo majhno procesorsko moč, kar omejuje velikost nevronskega omrežja. V diplomski nalogi je predstavljen sistem razpoznavanja besednih ukazov z uporabo konvolucijskega nevronskega omrežja. Nevronsko omrežje je bilo naučeno z vzorci, ki bodo povzročili prekomerno prileganje. Lastnost prekomernega prileganja se je uporabila za zviševanje natančnosti razpoznavanja. Izvedena je bila primerjava razpoznavanja vzorcev znanega govorca in vzorcev neznanega govorca. Primerjava je pokazala pozitivno lastnost prekomernega prileganja pri razpoznavanju besednih ukazov.

Language:Slovenian
Keywords:razpoznavanje besednih ukazov, strojno učenje, prekomerno prileganje
Work type:Bachelor thesis/paper
Organization:FE - Faculty of Electrical Engineering
Year:2023
PID:20.500.12556/RUL-149958 This link opens in a new window
COBISS.SI-ID:168706307 This link opens in a new window
Publication date in RUL:12.09.2023
Views:743
Downloads:36
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Secondary language

Language:English
Title:Embedded System for Speech Command Recognition Using a Convolutional Neural Network Model
Abstract:
Recognition of verbal commands is being used in numerous processes and devices. Numerous devices are built with microprocessors, which have small processing power, which limits the size of neural networks. The thesis presents a system for recognizing verbal commands using a convolutional neural network. The neural network was trained with patterns that will result in overfitting. The overfitting property was used to increase the recognition accuracy. A comparison of the recognition of patterns of a known speaker and patterns of an unknown speaker was performed. The comparison showed a positive overfitting property in recognition of verbal commands.

Keywords:recognition of verbal commands, machine learning, overfitting

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