Prepoznavanje akordov s skritim markovskim modelom

Abstract

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Language:	Slovenian
Year of publishing:	2013
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FRI - Faculty of Computer and Information Science
Publisher:	[S. Brus]
UDC:	004.9(043.2)
COBISS:	10156884
Views:	73
Downloads:	15
Average score:	0 (0 votes)
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Secondary language:	English
Secondary title:	Chord recognition with a hidden Markov model
Secondary abstract:	In this paper a system for automatic chord estimation of an input song is presented. Our system is based on a Hidden Markov model – HMM. Visual representation of HMM elements is offered. Metric called Chromagram is used for evaluation of system states. Learn and evaluation processes are presented. Our system learns rules and performs evaluation on Isophonics musical database. Our system achieves 62% classification accuracy using 10-fold validation. Chord alphabet, used in our model, contains 25 chord states. We present reasons for achieved results and perform detailed estimation analysis. Our approach contains knowledge of music theory and psychoacoustics. All methods, used in our system are argued and compared with modern systems. Further, some options for improving classification accuracy are presented.
Secondary keywords:	chord;hmm;mirex;fft;computer science;computer and information science;diploma;
File type:	application/pdf
Type (COBISS):	Bachelor thesis/paper
Thesis comment:	Univerza v Ljubljani, Fak. za računalništvo in informatiko
Pages:	63 str.
ID:	24207355