SMC / ICMC Summer School 2014
Topic: Computational Music Analysis
Athens, Greece, 11 - 14th September, 2014
The Sound and Music Computing summer school promotes interdisciplinary education and research in the field of Sound and Music Computing. It is aimed at graduate students working on their Master or PhD thesis, but it is also open to any person carrying out research in this field. The 2014 SMC Summer School will take place in Athens, Greece, right before the SMC/ICMC Conference, between the 11th and 14th of September 2014.
The topic of the summer school is Computational Music Analysis.
Background: One of the most important fields of sound and music computing is the study of the musical object itself, i.e. music analysis. Computational music analysis (CMA) is becoming more and more widespread, as computers can cope with extensive amounts of data, do comparative analyses of large musical corpora, and formalise the analytical process so that there are no gaps or hidden steps in the procedure. The area of computational music analysis bears close links to the area of Music Information Retrieval, though the aims of the former are more musicologically oriented, and the role of the human analyst can be considered indispensable, especially in the evaluation of the algorithmic outputs. The summer school will engage with analysis of the audio as well as discrete score representations and MIDI. It is aimed at both computer scientists and musicologists/composers alike.
Structure: The summer school will be divided into three parts.
1. Introductory part:
- Introductory lectures and workshop in music analysis – various methodologies such as semiotic analysis, reductionist approaches and motivic analysis. Emphasis on stylistic comparative approaches. Aimed mainly at computer scientists/engineers.
- Introductory tutorials on MIR systems for CMA: MARSYAS and MIR Toolbox. Aimed mainly at musicologists/musicians/composers.
- Introductory tutorial: Knowledge Representations and symbolic processing techniques for CMA. Aimed at both musicologists and computer scientists.
2. Presentation of aspects of computational music analysis, including melodic, rhythmic and harmonic.
3. Project-based learning: 4 Specific projects, two based on symbolic representations and two based on audio. Various musical corpora of different types of music will be available for analysis.
Maximum 20 participants will be selected to attend. If you are a PhD student in music information retrieval, musicology, music, music psychology, computer science, engineering, and related disciplines, you might find this summer school particularly exciting and helpful towards the completion of your degree. If you work in MIR, you might find that this year's musicological orientation of the summer school gives a new perspective to your current work. If you are a computer scientist or engineer, you will gain an understanding of music analysis methodologies and how to apply your skills in the analysis of music.
To apply: Please send a CV together with a covering letter explaining your motivation and experience to Christina Anagnostopoulou (chrisa at music dot uoa dot gr).
Deadline for applications: 31st of May, 2014. Applicants will be notified by the beginning of June whether their application has been successful, and will be required to register to the Summer School by June 10th, in order to secure their place.
Update: Applicants are strongly encouraged to apply as early as possible as we have already received a high number of applications, and early applications will be given priority.
The cost of attending the summer school, including lectures, training sessions, laboratory material and coffee breaks is 240€.
Tutors include the following (in alphabetical order):
- Christina Anagnostopoulou, University of Athens, Greece (contact person, chair)
- Emilios Cambouropoulos, Aristotle University of Thessaloniki, Greece
- Olivier Lartillot, Aalborg University, Denmark
- Alan Marsden, University of Lancaster, UK
- Aggelos Pikrakis, University of Peiraeus, Greece
- Costas Tsougras, Aristotle University of Thessaloniki, Greece
- George Tzanetakis, University of Victoria, Canada
- Anja Volk, Utrecht University, Netherlands
Short CVs of the teaching staff are appended below:
Christina Anagnostopoulou is an assistant professor of music informatics at the Department of Music Studies, University of Athens. She studied Music (Bmus Hons) and Artificial Intelligence (MSc) at the University of Edinburgh. Her PhD was on computational music analysis at the same University. She has previously taught at the Universities of Edinburgh, Glasgow and Queen's Belfast, where she became a permanent member of staff and led the Music Informatics and Cognition research group. She was a partner at the European Project MIROR and she is participating in a number of other European and National research projects.
Emilios Cambouropoulos is an associate professor of musical informatics at the School of Music Studies, Aristotle University of Thessaloniki. He studied physics, music and music technology, and obtained his PhD in 1998 on artificial intelligence and music at the University of Edinburgh. Emilios Cambouropoulos has published extensively in the domain of computational musicology on topics such as musical representation, melodic segmentation, note spelling, beat-tracking, rhythm perception, voice/stream separation, pattern recognition, melodic analysis, harmonic analysis, motivic categorisation. He is an associate/consulting editor in international journals, and board member of ESCOM and ICMPC. He is currently a partner in the EU project COINVENT: Concept Invention Theory, investigating aspects of musical creativity.
Olivier Lartillot is researcher in computational music analysis. He is finishing a 5-year Academy of Finland research fellowship at the University of Jyväskylä. He is the main designer of MIRtoolbox, a computational framework for audio and musical feature extraction from audio. He is releasing The MiningSuite, a new framework combining audio and symbolic analysis, and including pattern mining for motivic, metrical and structural analyses. He collaborates with the Swiss Center for Affective Sciences in projects related to music and emotion. He is co-instigator of CréMusCult project, funded by French ANR, an interdisciplinary study of traditional Mediterranean music culture.
Alan Marsden is a senior lecturer at the Lancaster Institute for the Contemporary Arts at Lancaster University, and editor of the Journal of New Music Research. His original training was in music analysis and he began to use computers in research in that field during his doctoral studies at Cambridge University. His research over the past 25 years has been directed towards formalisation of concepts from music theory with the twin aims of more intelligent musical software and better understanding of music. Recent research has focused on the computational analysis of musical structure, particularly software for Schenkerian analysis.
Aggelos Pikrakis is a lecturer at the Department of Informatics, University of Piraeus, Greece. His research interests include digital signal processing for music, audio and speech, and content-based music retrieval. He has co-authored two books with Academic Press (Elsevier Science): "Introduction to Pattern Recognition: a Matlab Approach (2010)" and "Introduction to Audio Analysis: a Matlab Approach" (2014), and has participated in several EU and national research programs. He is an editorial board member for the EURASIP Journal of Advances in Signal Processing (2008- ) and elected member of the Board of Directors of EURASIP (2011 - 2014). In MIREX-2013, he scored the first place in the Latin Genre Classification task.
Costas Tsougras (composer - music theorist) studied composition at the Thessaloniki New Conservatoire and musicology at the Aristotle University of Thessaloniki (bachelor and PhD) and the Columbia University of New York (where he worked with Fred Lerdahl on his PhD project involving the use of the Generative Theory of Tonal Music on 20th-century modal music). He is assistant professor of systematic musicology and music analysis at the School of Music of the A.U.Th. He has published theoretical and analytical work in international and Greek journals or conference proceedings on GTTM, Modal Pitch Space, music cognition models, computational musicology, music by Greek contemporary composers (Skalkottas, Xenakis, etc.).
George Tzanetakis is an Associate Professor in the Department of Computer Science with cross-listed appointments in ECE and Music at the University of Victoria, Canada. He is Canada Research Chair (Tier II) in the Computer Analysis and Audio and Music and received the Craigdaroch research award in artistic expression at the University of Victoria in 2012. In 2011 he was Visiting Faculty at Google Research. He received his PhD in Computer Science at Princeton University in 2002 and was a Post-Doctoral fellow at Carnegie Mellon University in 2002-2003. His research spans all stages of audio content analysis such as feature extraction,segmentation, classification with specific emphasis on music information retrieval.
Anja Volk holds master degrees in musicology and mathematics and received her PhD in computational musicology from Humboldt University of Berlin in 2002. After two post-doc periods at the University of Southern California and Utrecht University, she has been awarded a prestigious VIDI grant from the Netherlands Organisation for Scientific Research in 2010, which allowed her to start her own interdisciplinary research group MUSIVA as an assistant professor at Utrecht University on the topic of music similarity. Her research interests and publications embrace Music Information Retrieval, Music Cognition, Computational Music Analysis, Mathematical Music Theory, Performance Theory and Computational Humanities.She is a board member of the Society for Mathematics and Computation in Music and of the International Society for Music Information Retrieval.
Summer School organising committee:
Christina Anagnostopoulou and Aggelos Pikrakis (chairs), Anja Volk, Emilia Gomez.
Further information and Inscription:
Please email Christina Anagnostopoulou on email@example.com