DocumentCode
3401983
Title
Large corpus of Iranian music
Author
Shirali-Shahreza, M.H. ; Shirali-Shahreza, Sajad
Author_Institution
Virtual Educ. Grad. Coll., Amirkabir Univ. of Technol., Tehran, Iran
fYear
2009
fDate
14-17 Dec. 2009
Firstpage
568
Lastpage
573
Abstract
Digital music is now widely used and a great number of digital music files are available on the Internet. Designing systems that can automatically index, search and retrieve the digital music is one of the active research fields. One of the requirements for design and evaluation of such systems is corpuses of digital music samples. A good corpus is expected to have a number of features such as including a great number of samples, have samples of different artists and also samples with different quality. Additionally, the regional music of different parts of the world uses local musical instruments which results in music that are acoustically different. So, corpuses of regional music are needed for design and evaluation of web scale systems. Considering the above reasons, we created a large corpus of Iranian music. In this paper, we review available public music corpuses and then describe our corpus. Our corpus contains 27496 music tracks of 1355 artists that gathered from the Internet. The lyrics for more than 54% of tracks are also provided. We analyze the different aspects of collected tracks such as their bit rate and sampling rate which are helpful in designing large scale systems.
Keywords
Internet; music; Internet; Iranian music; Web scale systems; digital music files; local musical instruments; Databases; Educational institutions; Indexing; Internet; Mel frequency cepstral coefficient; Mobile handsets; Music information retrieval; Recommender systems; Search engines; System testing; Corpus; Diversity; Iranian Music; Mel Frequency Cepstral Coefficients (MFCC); Music Track;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Information Technology (ISSPIT), 2009 IEEE International Symposium on
Conference_Location
Ajman
Print_ISBN
978-1-4244-5949-0
Type
conf
DOI
10.1109/ISSPIT.2009.5407527
Filename
5407527
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