Computational Ethnomusicology: perspectives and challenges

Since the beginning of Music Information Retrieval (MIR) as a field, most of its models and technologies have been developed for mainstream popular music in the so-called ‘Western’ tradition. Over the last few years, there has been an increasing interest in applying available techniques to the study of traditional, folk or ethnic music. Ethnomusicologists, music theorists and practitioners, among others, could considerably benefit from this research. Although computational techniques have been proved to be of great interest when applied to different musical repertoires, it is apparent that we need to develop culturespecific techniques and algorithms to understand, model, and process different music repertoires. The name of Computational Ethnomusicology can be as old as 34 years at least (Halmos et al. 1978). Halmos et al. (1978), two mathematicians and an engineer, provide an interesting discussion about the role of computers in the main five areas of research in ethnomusicology: data collection, administration, notation, selection and systematization, and scientific treatment. According to them, computers cannot be used for collecting data, as field work and personal meeting with informers is an integral part of data gathering. In addition, in the area of scientific treatment the computer might be equally limited, as they might not understand human and historical behaviours expressed in the data. However, they explore the use of computers for research-administration, notation, selection and systematization from three groups of data: melodies (the study involves 10,000 melodies), registrations and social conditions. We see that, although these principles and usages of computers are still valid today, computational models can also be used to collect data in the field, or to compute models of social interaction that is based on complex networks science. The term was recently re-defined by Tzanetakis et al. (2007) as ‘the design, development and usage of computer tools that have the potential to assist in ethnomusicological research’. Under this view there is a main discipline, Ethnomusicology, that takes advantage of advances in supportive disciplines such as Computer Science, Music Cognition or Cultural Studies and applies/tune them to their own problems. Even though this could be the most accepted and practiced view, and the papers we include here totally adhere to it, we would like to note that this is a restrictive definition of a discipline as tool-provider. Computer models can be ‘theories’or ‘hypotheses’ (not just ‘tools’as a spreadsheet or a statistical package can be) about processes and problems studied by traditional ethnomusicologists. When we approach Computational Ethnomusicology this way, we adopt a new mental framework that helps to restructure problems and perceive the relationships between their constitutive elements under a different perspective. We look forward in that the present special issue may help to step ahead towards such a procedural view of the computations required in the discipline. As publications in the topic of Computational Ethnomusicology have been scattered among different journals, the goal of this special issue is to gather relevant, high-quality research on computational methods and applications in ethnomusicology. The papers included here deal with different musical facets such as pitch, pulse and tempo, and voice timbre. They address different musical repertoires, from Central-African to Basque folk music. They also cover a broad area: tools, including data collections, methodology and Ethnomusicology core-problems. It is noticeable that the latter category is barely represented. Maybe this could just be a side-effect of the journal hosting the call, a bias induced by the invited editors and reviewers, or maybe an indication (or confirmation) that the field is still very young. In that case, it is clear that there first needs to be procedural recipes and computational weapons that give us the power to address all the open problems. The paper titled Tarsos, a Modular Platform for precise Pitch Analysis of Western and non-Western music, by Joren Six et al., presents a tool for automatic pitch content description of music signals conceived to cope with different music traditions. Pitch-content information is in the core of melody, tuning, scale and tonality characterization. The Tarsos platform integrates several state-of-the-art pitch estimation algorithms and provides different visualization facilities, e.g. pitch estimations, pitch and pitch-class histograms (related to the used scale) and histogram peaks, representative of the main intervals. The tool also provides input/output and scripting capabilities. The authors show some examples of the use of Tarsos for different analysis tasks in non-Western music, focusing on problematic issues such as the integration or comparison of different pitch estimation algorithms, music with pitch drift, and the analysis of large datasets (e.g. Makkam recognition). In this study, an important conclusion is that we can build generalized approaches for pitch distribution analysis that can go beyond elementary concepts of the Western music theoretical canon by avoiding music theoretical concepts. Although these tools are useful for low-level musical analysis, they would eventually need manual tuning and interpretation by experts on the specific repertoire under study.