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Title:Analiza in klasifikacija zvočnih posnetkov v programskem okolju Python : diplomsko delo
Authors:ID Rantuša, Lara (Author)
ID Podgorelec, Vili (Mentor) More about this mentor... New window
Files:.pdf UN_Rantusa_Lara_2022.pdf (2,29 MB)
MD5: 633DA226F0042548312721ECC81A101B
 
Language:Slovenian
Work type:Bachelor thesis/paper (mb11)
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu obravnavamo okolje in orodja v programskem jeziku Python za obdelavo, analizo in klasifikacijo zvočnih posnetkov. Razložene so lastnosti glasbe in kako se te zaznavajo z naravno in računalniško analizo zvoka. Opisan je postopek izdelave programa in uporabljeni algoritmi za strojno učenje, ki zna zvočne posnetke obdelati, analizirati in klasificirati glede na njihovo glasbeno zvrst ter na posnetku prepoznati število izvajalcev.
Keywords:analiza zvočnih posnetkov, klasifikacija zvočnih posnetkov, programsko okolje Python
Year of publishing:2022
Place of performance:Maribor
Publisher:[L. Rantuša]
Number of pages:1 spletni vir (1 datoteka PDF (VIII, [49] f.))
Source:Maribor
PID:20.500.12556/DKUM-81567 New window
UDC:004.85:004.93(043.2)
COBISS.SI-ID:109381635 New window
Publication date in DKUM:27.05.2022
Views:250
Downloads:77
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:15.04.2022

Secondary language

Language:English
Title:Analysis and classification of sound recordings in the Python programming environment
Abstract:In this work we examine the envirnoment and tools in the Python programming language for processing, analysis and classification of sound recordings. There are different features of music explained and how they are perceived by natural and computer analysis of sound. Described is the process of creating the program and the algorithms used for the machine learning, which can process, analyze and classify sound recordings according to other musical genre and identify the number of performers in the recording.
Keywords:analysis of sound recordings, classification of sound recordings, the Python software environment


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