Papers by Dimitrios Smailis
International Computer Music Conference, 2025
This article provides details on the implementation and design of the 'Make Your Own Band' softwa... more This article provides details on the implementation and design of the 'Make Your Own Band' software suite, a suite of standalone software applications utilizing machine learning (ML) and music information retrieval (MIR) developed for use in school classrooms. Preliminary results through testing, surveying, and interviewing music teachers suggest that the system holds significant promise for advancing music education. It could promote inclusion through kinesthetic and gestural methods, has the potential to simplify music activities, address instrument shortages in resourcelimited environments, enhance participation, and increase student engagement.
Digital Culture & Audio Visual Challenges, 2025
This survey-based research is part of our broader research activity concerning machine learning (... more This survey-based research is part of our broader research activity concerning machine learning (ML) software, which we are developing for use in music education. With the ultimate goal of informing the design of our software, last academic year, we conducted a quantitative study using a questionnaire addressed to music teachers working in public music schools and conservatories in Greece. Through this research, we examined teachers' habits and perceptions regarding the use of digital music technology (DMT) and artificial intelligence (AI) in music teaching, as well as their views on the role of kinesthetic activity in the music classroom. The analysis of the results yielded important findings that help us piece together the puzzle of the needs of a highly kinesthetic and musically rich classroom, which ML software could support and transform. Among the key findings, a substantial proportion of teachers reported access to computers and viewed DMT as beneficial for teaching, although few currently integrate ML or AI applications into their lessons. Despite this limited use, teachers expressed openness to adopting such tools, provided that adequate support is available, and highlighted the practical constraints of their daily school routines. Statistical analyses showed a strong positive association between perceived kinesthetic benefits and participation and inclusion, while correlations between demographic factors and attitudes were generally small.
European journal of engineering and technology research, Dec 29, 2023
In music education, there are several cases where the instructor needs to set preparatory tasks a... more In music education, there are several cases where the instructor needs to set preparatory tasks and use verbal communication, both of which, nonetheless, interrupt the music continuity. These "interruptions" are considered as learning barriers. Having researched teaching communication habits on several music instruction cases, we have come up with the idea of designing a set of software blocks that, laid down together as a digital aid to the class, can generously assist music teaching by providing communication facilitators in a wide range of commonly used music teaching exercise tasks. In this direction, a range of algorithms and software blocks have been implemented at the Ionian University using the Max/MSP TM dedicated software platform, comprising the FIG set of tools. A specific subset of these software tools has included Machine Learning (ML) logic in order to promote a wiser instructor-student communication that advances class musicality and potentially facilitates deeper consolidation of musical structures.
This work looks at improvisations produced by the OMax, ImproteK, and Djazz ML generators, throug... more This work looks at improvisations produced by the OMax, ImproteK, and Djazz ML generators, through the lens of the elements of music and suggests a musically-oriented evaluation methodology. This idiomatic music analysis is presented from a jazz performer's point of view, reflecting upon cognitive foundations of emotion and meaning. The analysis, based mainly on the evaluation of already published material and on the authors' own experiments, shows musical drawbacks in terms of tension and release of the resulting melodic lines, voice leading of chords, rhythm, groove, dynamic control, and structure.
2nd Conference on AI Music Creativity (MuMe + CSMC), Jul 18, 2021
This work looks at improvisations produced by the OMax, ImproteK, and Djazz ML generators, throug... more This work looks at improvisations produced by the OMax, ImproteK, and Djazz ML generators, through the lens of the elements of music and suggests a musically-oriented evaluation methodology. This idiomatic music analysis is presented from a jazz performer's point of view, reflecting upon cognitive foundations of emotion and meaning. The analysis, based mainly on the evaluation of already published material and on the authors' own experiments, shows musical drawbacks in terms of tension and release of the resulting melodic lines, voice leading of chords, rhythm, groove, dynamic control, and structure.
1ο Πανελλήνιο Συνεδρίου Καλλιτεχνικής Παιδείας: «Όπου ακούς μουσική...». Πάτρα 18-20/6/2015 ΠΡΑΚΤΙΚΑ ΣΥΝΕΔΡΙΟΥ, 2015
Η συγκεκριμένη εργασία αφορά την ανάπτυξη μεθόδων διδασκαλίας και τη χρήση εργαλείων της βοηθητικ... more Η συγκεκριμένη εργασία αφορά την ανάπτυξη μεθόδων διδασκαλίας και τη χρήση εργαλείων της βοηθητικής μουσικής τεχνολογίας στο μάθημα της μουσικής. Στόχος της είναι η ένταξη και η συμπερίληψη των μαθητών με κινητικές αναπηρίες στο μάθημα της μουσικής μέσω της διαφοροποίησης του. Σκοπός της είναι η παροχή πληροφοριών σε δασκάλους για τη δημιουργία ασφαλούς μαθησιακού περιβάλλοντος στο οποίο οι συγκεκριμένοι μαθητές θα μπορούν να αναπτύξουν τη δυναμική των ικανοτήτων τους. Για τη παραδειγματική χρήση της βοηθητικής μουσικής τεχνολογίας χρησιμοποιείται εκπαιδευτικό σενάριο μαθητή με αναπηρία (τετραπληγία).
Drafts by Dimitrios Smailis
A highly controversial entrance of Artificial Intelligence (AI) music generators in the world of ... more A highly controversial entrance of Artificial Intelligence (AI) music generators in the world of music composition and performance is currently advancing. A fruitful research from Music Information Retrieval, Neural Networks and Deep Learning, among other areas, are shaping this future. Embodied and non-embodied AI systems have stepped into the world of jazz in order to co-create idiomatic music improvisations. But how musical these improvisations are? This dissertation looks at the resulted melodic improvisations produced by OMax, ImproteK and Djazz (OID) AI generators through the lens of the elements of music and it does so from a performer’s point of view. The analysis is based mainly on the evaluation of already published results as well as on a case study I carried out during the completion of this essay which includes performance, listening and evaluation of generated improvisations of OMax. The essay also reflects upon philosophical issues, cognitive foundations of emotion and meaning and provides a comprehensive analysis of the functionality of OID.
Uploads
Papers by Dimitrios Smailis
Drafts by Dimitrios Smailis