Your browser does not allow JavaScript!
JavaScript is necessary for the proper functioning of this website. Please enable JavaScript or use a modern browser.
|
|
SLO
|
ENG
|
Cookies and privacy
DKUM
EPF - Faculty of Business and Economics
FE - Faculty of Energy Technology
FERI - Faculty of Electrical Engineering and Computer Science
FF - Faculty of Arts
FGPA - Faculty of Civil Engineering, Transportation Engineering and Architecture
FKBV - Faculty of Agriculture and Life Sciences
FKKT - Faculty of Chemistry and Chemical Engineering
FL - Faculty of Logistic
FNM - Faculty of Natural Sciences and Mathematics
FOV - Faculty of Organizational Sciences in Kranj
FS - Faculty of Mechanical Engineering
FT - Faculty of Tourism
FVV - Faculty of Criminal Justice and Security
FZV - Faculty of Health Sciences
MF - Faculty of Medicine
PEF - Faculty of Education
PF - Faculty of Law
UKM - University of Maribor Library
UM - University of Maribor
COBISS
Ekonomsko poslovna fakulteta
Fakulteta za kmetijstvo
Fakulteta za logistiko
Fakulteta za organizacijske vede
Fakulteta za varnostne vede
Fakulteta za zdravstvene vede
Knjižnica tehniških fakultet
Medicinska fakulteta
Miklošičeva knjižnica - FPNM
Pravna fakulteta
Univerzitetna knjižnica Maribor
Bigger font
|
Smaller font
Introduction
Search
Browsing
Upload document
Statistics
Login
First page
>
Show document
Show document
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...
Files:
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
UDC:
004.85:004.93(043.2)
COBISS.SI-ID:
109381635
Publication date in DKUM:
27.05.2022
Views:
250
Downloads:
77
Metadata:
Categories:
KTFMB - FERI
Cite this work
Plain text
BibTeX
EndNote XML
EndNote/Refer
RIS
ABNT
ACM Ref
AMA
APA
Chicago
Harvard
IEEE
ISO 690
MLA
Vancouver
:
Average score:
(0 votes)
Your score:
Voting is allowed only for
logged in
users.
Share:
AddThis uses cookies that require your consent.
Edit consent...
Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.
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
Comments
Leave comment
You must
log in
to leave a comment.
Comments (0)
0 - 0 / 0
There are no comments!
Back
