ΕΥΡΩΠΑΪΚΗ ΕΝΩΣΗ
ΚΥΠΡΙΑΚΗ ΔΗΜΟΚΡΑΤΙΑ
Η ΔΕΣΜΗ 2009-2010 ΣΥΓΧΡΗΜΑΤΟΔΟΤΕΙΤΑΙ ΑΠΟ ΤΗΝ ΚΥΠΡΙΑΚΗ ΔΗΜΟΚΡΑΤΙΑ
ΚΑΙ ΤΟ ΕΥΡΩΠΑΪΚΟ ΤΑΜΕΙΟ ΠΕΡΙΦΕΡΕΙΑΚΗΣ ΑΝΑΠΤΥΞΗΣ ΤΗΣ ΕΕ
DESMI 2009-2010 IS CO-FUNDED BY THE REPUBLIC OF CYPRUS AND THE EUROPEAN REGIONAL DEVELOPMENT FUND
ΕΞΑΜΗΝΙΑΙΑ ΕΚΘΕΣΗ ΠΡΟΟΔΟΥ ΕΡΕΥΝΗΤΙΚΟΥ ΕΡΓΟΥ ΤΗΣ ΔΕΣΜΗΣ 2009-2010
SIX MONTH PROGRESS REPORT FOR RESEARCH PROJECT FUNDED BY DESMI 20092010
1. ΓΕΝΙΚΑ ΣΤΟΙΧΕΙΑ ΕΡΓΟΥ / GENERAL PROJECT INFORMATION
Αρ. Πρωτ. Έργου
Project Protocol Number
Τίτλος Έργου
Project Title
Συντονιστής Έργου
Project Coordinator
Ανάδοχος Φορέας
Host Organisation
Περίοδος Έκθεσης
Reporting Period
Ανθρωπιστικες/Ανθρω/0311(ΒΕ)/19
Intelligent system for the identification of similarities and differences between the GreekCypriot, Greek, Turkish-Cypriot, and Turkish folk music
Prof. Christos N. Schizas
University of Cyprus - Dep. of Computer
Science
ΑΠΟ
FROM
1/10/2012
Ημερ. Έναρξης
1/04/2012
Starting Date
Διάρκεια Έργου
36 months
Project Duration
ΜΕΧΡΙ
1/4/2013
TO
2. ΠΡΟΟΔΟΣ ΥΛΟΠΟΙΗΣΗΣ ΕΡΓΟΥ / PROJECT IMPLEMENTATION PROGRESS
Δέσμες Εργασίας που Ολοκληρώθηκαν
Completed Work-Packages
Παραδοτέα Έργου που Ολοκληρώθηκαν
Completed Deliverables
WP 3
Internal report and Data collection
During the period from October 2012 to March 2013, two meetings were held/organized by the Project Coordinator and most of other
members of the consortium of the project. In the first meeting was held on 29.11.2012 and the following members were
present:Andreas Neocleous, Maria Panteli, Michalis Terlikkas and Giannis Zavros.
Giannis Zavros is a musician who is a master of Cyprus pithkiavli (πυθκιάβλι), the violin and the lute (λαούτο). He joined this meeting
to perform traditional tunes to be recorded and also to share his knowledge on folk music and local instruments. The main purpose of
the first meeting was to introduce the project to Cypriot music expert and member of our project team, Michalis Terlikkas and discuss
the particularities of the music. Also to record some traditional tunes as a first attempt, so that any technical or other problems will be
identified early enough and be rectified. The recording session involved mainly Giannis Zavros, who performed traditional tunes on
the lute, violin and pithkiavli. During the session he also explained how he learned to play these instruments and how he made and
tuned his pithkiavli.
In the second meeting was held on 21.03.2013 and the following members were present:Andreas Neocleous, Maria Panteli and
Michalis Terlikkas. The purpose of this meeting was to inform Michalis Terlikkas about the progress of the project and discuss
musicological issues that are important for the subsequent progress of the project. The latest research results were presented,
followed by a short discussion for the subsequent steps. Then the discussion was shifted to music and particularly to the music
tradition of the so-called Fones (φωνές) (singular Foni (φωνή)). Michalis Terlikkas provided insights on the definition and the number
of the different Fones as well as on the available literature on the topic.
During the last six months, the state of the art on signal processing techniques as well as computational intelligence techniques for
music analysis and classification were studied in an internal report. This study will be presented to the members of the group and the
presentation is organized to take place in the University of Cyprus on Wednesday 10.4.13. We invited Nicolai Petkov to participate in
the group meeting and he visited Cyprus for this purpose. New algorithms in MATLAB were attempted as they are available in
numerous websites. More specifically, the algorithms we used helped to analyze Cypriot folk music in a two stage process. In the first
stage, a number of low-level features had been extracted from the audio files using a sliding window. Each song had been
segmented into approximately 13000 frames of 1024 bins length. For each frame, the algorithm extracts 18 tonal features and keeps
the mean and the standard deviation of each feature, thus creating a vector of 36 features for each song. In a second stage, called
the classification stage, the algorithm creates n-fold databases and for each fold it creates several models with artificial neural
networks (ANN). In every iteration the algorithm builds one model with ANN and a number of different parameters of the ANN are
being used. The purpose of this algorithm is to let the system build a large number of models by systematically changing several
parameters in order to achieve and identify a model that will better discriminate the classes in a supervised modeling manner. An
extended abstract of this work has been submitted in to the International Workshop on Folk Music Analysis to be held in Amsterdam
on June 6 and 7, 2013 and accepted for poster presentation. More specifically, a database of 106 monophonic songs was used. The
20 songs were Cypriot folk songs performed by Cypriot folk musician Andreas Gristakkos. The remaining of the 86 songs were
consisted of 43 western songs and solo improvisations, as well as 43 Turkish makams. The features used were the 1) RMS-mean, 2)
RMS-standard deviation, 3) Zero crossing rate - mean, 4) Zero crossing rate - standard deviation, 5) Spectral centroid - mean, 6)
Spectral centroid - standard deviation 7) Roll off - mean, 8) Roll off - standard deviation 9) Entropy - mean, 10) Entropy - standard
deviation, 11-23) Mel frequency cepstrum coefficients (13 coefficients) - mean, 24-36) Mel frequency cepstrum coefficients (13
coefficients) - standard deviation. In a following step, the dataset was separated into a “training set” and “validation set”. The training
set was consisted of 32 western songs and 33 Turkish songs. The validation set was consisted of 13 western, 11 Turkish and 20
Cypriot songs. We built models with supervised learning using ANNs with one hidden layer, K-nearest neighbour with 1-nearest
neighbour, and support vector machines with kernels 1, 2 and 3. 60% of the Cypriot songs were classified by the models to be very
close to the Turkish music while 30% of the Cypriot songs were classified in the same distance between Turkish and Western. From
the results, we concluded that the 18 tonal features were able to completely discriminate the Western from the Turkish music during
training and to classify correctly 92% of the western music and 100% of the Turkish music in a “blind” set. Considering the tonal
features used for creating such models, the Cypriot songs are more likely to share tonal similarities with the Turkish music.
Moreover, a comprehensive study and collection of the traditional and folk music of Cyprus has been done and recorded. The
recorded material are reported in an .xls format and uploaded in the website.
3. ΠΡΟΒΛΗΜΑΤΑ ΠΟΥ ΠΑΡΟΥΣΙΑΣΤΗΚΑΝ / PROBLEMS ENCOUNTERED
There was a technical problem on uploading the audio material (data) on the website because of the large size of the
file. We are in touch with the technicians in order to solve the problem and as soon it is solved, it will be reported.
4. ΥΛΟΠΟΙΗΣΗ ΠΡΟΫΠΟΛΟΓΙΣΜΟΥ / BUDGET IMPLEMENTATION
Συνολικός Προϋπολογισμός Έργου
Total Project Budget
Ύψος Επιχορήγησης που καταβλήθηκε από το ΙΠΕ μέχρι στιγμής
Funding Received from RPF so far
Ύψος Συνόλου Δαπανών μέχρι στιγμής
Actual Expenses Incurred so far
99300 ΕΥΡΩ/EUR
34755ΕΥΡΩ/EUR
32161,21ΕΥΡΩ/EUR
5. ΣΧΟΛΙΑ ΙΠΕ / RPF COMMENTS
Μόνο για χρήση από το ΙΠΕ. Παρακαλώ μη συμπληρώνετε .
For RPF internal use only. Please do not complete.
Αρμόδιος Λειτουργός ΙΠΕ
RPF Project Officer
Ημερ/νια
Date
Σημείωση: Η συλλογή και επεξεργασία δεδομένων προσωπικού χαρακτήρα που περιέχονται στις Εκθέσεις
Προόδου οι οποίες υποβάλλονται στο ΙΠΕ για έλεγχο του οικονομικού & επιστημονικού αντικειμένου του
Έργου, γίνεται με εμπιστευτικότητα και σύμφωνα με τον περί Επεξεργασίας Δεδομένων Προσωπικού
Χαρακτήρα (Προστασία του Ατόμου) Νόμο του 2001 και τον Κανονισμό του ΙΠΕ σε Σχέση με τη Συλλογή,
Επεξεργασία και Χρήση Δεδομένων Προσωπικού Χαρακτήρα, ο οποίος βρίσκεται αναρτημένος στην
ιστοσελίδα του Ιδρύματος (www.research.org.cy).