Music Information Retrieval Techniques for Determining the Place of Origin of a Music Interpretation

被引：0

作者：

Kiska, Tomas ^{[1
,2
,3
]}

Galaz, Zoltan ^{[1
,2
,4
]}

Zvoncak, Vojtech ^{[1
,2
]}

Mucha, Jan ^{[1
,2
]}

Mekyska, Jiri ^{[1
,2
]}

Smekal, Zdenek ^{[1
,2
]}

机构：

[1] Brno Univ Technol, Dept Telecommun, Tech 10, Brno 61600, Czech Republic

[2] Brno Univ Technol, Res Ctr 6, Tech 10, Brno 61600, Czech Republic

[3] Masaryk Univ, Cent European Inst Technol, Multimodal & Funct Neuroimaging Res Grp, Kamenice 5, Brno 62500, Czech Republic

[4] Masaryk Univ, Cent European Inst Technol, Appl Neurosci Res Grp, Kamenice 5, Brno 62500, Czech Republic

来源：

2018 10TH INTERNATIONAL CONGRESS ON ULTRA MODERN TELECOMMUNICATIONS AND CONTROL SYSTEMS AND WORKSHOPS (ICUMT 2018): EMERGING TECHNOLOGIES FOR CONNECTED SOCIETY | 2018年

关键词：

music analysis; musical features; feature calculation; music synchronization; dynamic time warping; audio-to-audio alignment; music information retrieval; TOOLBOX; TIME;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Determining the place of origin of the musical compositions is a modern area of research in the field of music information retrieval (MIR). The musical interpretation of one piece carries a variety of author's intentions that influence the musical character of the resulting composition. These aspects may include rhythm, dynamics, timbre, or tonality. This paper introduces a novel methodology for determining the place of origin of a music interpretation based on advanced signal processing and machine learning techniques. For this purpose, we collected a database of 35 different interpretations of Leos Janacek's String Quartet No. 1, "Kreutzer Sonat": IV. Con Moto - Adagio. Employing random forests classifier, we achieved classification accuracy over 97% using features derived from Mel-frequency cepstral coefficients. This paper proves it is possible to use MRI for determining the origin of a music interpretation with very high accuracy.

引用

页数：5

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