Maximos Kaliakatsos-Papakostas

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• PhD
• Associate Professor at Hellenic Mediterranean University

A novel 3D auto-drum machine system for the generation and recording of percussion sounds is developed and presented. The capabilities of the machine, along with a calibration, sound production, and collection protocol are demonstrated. The sounds are generated by a drumstick at pre-defined positions and by known impact forces from the programmable...

The Department of Music Technology and Acoustics of the Hellenic Mediterranean University offers a unique higher education program in Greece, addressing the growing demand for specialists in music technology, sound technology, and acoustics. It aims to educate specialized professionals in the rapidly advancing scientific fields of music technology...

This paper presents a methodology for generating cross-harmonizations of jazz standards, i.e., for harmonizing the melody of a jazz standard (Song A) with the harmonic context of another (Song B). Specifically, the melody of Song A, along with the chords that start and end its sections (chord constraints), are used as a basis for generating new har...

Studying under-represented music traditions under the MIR scope is crucial, not only for developing novel analysis tools, but also for unveiling musical functions that might prove useful in studying world musics. This paper presents a dataset for Greek Traditional and Folk music that includes 1570 pieces, summing in around 80 hours of data. The dat...

This paper presents a system that automates activation of events that improve the accessibility and enhance the experience in theatrical performances in real time and proposes and evaluates the core method employed therein. This method aligns a given set of subtitles that is created and synchronized by experts for a given “rehearsal” audio stream,...

This paper presents current developments taking place in the context of the MusiCoLab project. MusiCoLab aims at delivering a comprehensive and efficient web platform for music learning and teaching, by building on prior research experience of project partners, as well as by investigating the integration of state-of-the-art tools in intelligent mus...

Despite the fact that in some areas of cultural life, as in the case of certain online video platforms or TV programs, notable progress has been made to provide content accessible to Deaf and Hard of Hearing people (DHH), the same cannot be said for live theater performances. In this work, a system called NLP-Theatre is presented , with the emphasi...

Guitar tablature transcription consists in deducing the string and the fret number on which each note should be played to reproduce the actual musical part. This assignment should lead to playable string-fret combinations throughout the entire track and, in general, preserve parsimonious motion between successive combinations. Throughout the histor...

The field of automatic music composition has seen great progress in recent years, specifically with the invention of transformer-based architectures. When using any deep learning model which considers music as a sequence of events with multiple complex dependencies, the selection of a proper data representation is crucial. In this paper, we tackle...

This chapter discusses musical similarity focusing on issues of representation and processing of patterns in symbolic music data. Various facets of musical similarity are explored that pertain to practical problems encountered when developing formal models for pattern identification and induction in musical corpora; the representation of musical da...

This handbook is currently in development, with individual articles publishing online in advance of print publication. At this time, we cannot add information about unpublished articles in this handbook, however the table of contents will continue to grow as additional articles pass through the review process and are added to the site. Please note...

[This corrects the article DOI: 10.1371/journal.pone.0244964.].

The field of automatic music composition has seen great progress in recent years, specifically with the invention of transformer-based architectures. When using any deep learning model which considers music as a sequence of events with multiple complex dependencies, the selection of a proper data representation is crucial. In this paper, we tackle...

In this chapter, recent research in the domain of melodic harmonization and computational creativity is presented with a view to highlighting strengths and weaknesses of the classical cognitively inspired symbolic AI approach (often in juxtaposition to contemporary deep learning methodologies). A modular melodic harmonization system that learns cho...

CHAMELEON is a computational melodic harmonization assistant. It can harmonize a given melody according to a number of independent harmonic idioms or blends between idioms based on principles of conceptual blending theory. Thus, the system is capable of offering a wealth of possible solutions and viewpoints for melodic harmonization. This study inv...

Jazz improvisation on a given lead sheet with chords is an interesting scenario for studying the behaviour of artificial agents when they collaborate with humans. Specifically in jazz improvisation, the role of the accompanist is crucial for reflecting the harmonic and metric characteristics of a jazz standard, while identifying in real-time the in...

Previous research conducted on the cross-cultural perception of music and its emotional content has established that emotions can be communicated across cultures at least on a rudimentary level. Here, we report a cross-cultural study with participants originating from two tribes in northwest Pakistan (Khow and Kalash) and the United Kingdom, with b...

The objective of our research is to investigate new digital techniques and tools, offering the audience innovative, attractive, enhanced and, at the same time, accessible experiences. The project focuses on performing arts, particularly theatre, aiming at designing, implementing, experimenting and evaluating technologies and tools that expand the s...

This paper presents an experiment designed to investigate the influence of a creativity support tool on music creation. Twenty five participants were asked to harmonise two very similar melodies, the first on their own and the second while given the opportunity to interact with the CHAMELEON harmonisation assistant. CHAMELEON can offer a variety of...

Conceptual Blending (CB) theory discusses a basic mechanism that allows humans to understand and generate creative artefacts. CB theory has been primarily employed as a method for interpreting creative ideas and pieces of art, while recently algorithmic frameworks have been developed for methodologies that do generative use of CB towards achieving...

Machine Learning has been shown a successful component of methods for Automatic Music Composition (AMC). Considering music as a sequence of events with multiple complex dependencies on various levels of a composition, the Long Short-Term Memory-based (LSTM) architectures have been proven to be very efficient in learning and reproducing musical styl...

Conceptual Blending (CB) theory describes the cognitive mechanisms underlying the way humans process the emergence of new conceptual spaces by blending two input spaces. CB theory has been primarily used as a method for interpreting creative artefacts, while recently it has been utilised in the context of computational creativity for algorithmic in...

Conceptual Blending (CB) theory has been primarily employed as a method for interpreting creative artefacts, while recently it has been used as a creative tool for the algorithmic invention of new concepts. In music, interesting examples have been presented where low-level musical information (e.g. chord roots, chord types or pitch classes) is comb...

Considering music as a sequence of events with multiple complex dependencies, the Long Short-Term Memory (LSTM) architecture has proven very efficient in learning and reproducing musical styles. However, the generation of rhythms requires additional information regarding musical structure and accompanying instruments. In this paper we present DeepD...

We present a web-based real-time application that enables gestural interaction with virtual instruments for musical expression. Skeletons of the users are tracked by a Kinect sensor, while the performance of the virtual instruments is accomplished using gestures inspired from their corresponding physical counterparts. The application supports the v...

Long Short-Term Memory (LSTM) neural networks have been effectively applied on learning and generating musical sequences, powered by sophisticated musical representations and integrations into other deep learning models. Deep neural networks, alongside LSTM-based systems, learn implicitly: given a sufficiently large amount of data, they transform i...

This article presents the CHAMELEON melodic harmonisation assistant that utilises the principles of conceptual blending theory as a means for the invention of hybrid or novel harmonic idioms and an empirical evaluation of a number of computer-generated melodic harmonisation blends. Melodies originating from various idioms were harmonised either acc...

This chapter presents the CHAMELEON melodic harmonisation assistant that learns different aspects of harmony from expert-annotated data, blends learnt harmonies from different idioms using the COINVENT framework and harmonises user-given melodies. The learnt harmonic elements include chord types, chord transitions, cadences and bass voice leading,...

This book introduces a computationally feasible, cognitively inspired formal model of concept invention, drawing on Fauconnier and Turner's theory of conceptual blending, a fundamental cognitive operation. The chapters present the mathematical and computational foundations of concept invention, discuss cognitive and social aspects, and further desc...

Algorithmic music composition has long been in the spotlight of music information research and Long Short-Term Memory (LSTM) neural networks have been extensively used for this task. However, despite LSTM networks having proven useful in learning sequences, no methodology has been proposed for learning sequences conditional to constraints, such as...

In computational creativity, new concepts can be invented through conceptual blending of two independent conceptual spaces. In music, conceptual blending has been primarily used for analysing relations between musical and extra-musical elements in composed music rather than generating new music. This paper presents a probabilistic melodic harmonisa...

THE COGNITIVE THEORY OF CONCEPTUAL BLENDING may be employed to understand the way music becomes meaningful and, at the same time, it may form a basis for musical creativity per se. This work constitutes a case study whereby conceptual blending is used as a creative tool for inventing musical cadences. Specifically, the perfect and the renaissance P...

Conceptual blending when used as a creative tool combines the features of two input spaces, generating new blended spaces that share the common structure of the inputs, as well as different combinations of their non-common parts. In the case of music, conceptual blending has been employed creatively, among others, in generating new cadences (pairs...

How can harmony in diverse idioms be represented in a machine learning system and how can learned harmonic descriptions of two musical idioms be blended to create new ones? This paper presents a creative melodic harmonisation assistant that employs statistical learning to learn harmonies from human annotated data in practically any style, blends th...

Melodic harmonisation is a sophisticated creative process that involves deep musical understanding and a specialised knowledge of music relating to melodic structure, harmony, rhythm, texture, and form. In this article a new melodic harmonisation assistant is presented that is adaptive (learns from data), general (can cope with any tonal or non-ton...

Sound events are proven to have an impact on the emotions of the listener. Recent works on the field of emotion recognition from sound events show, on one hand, the possibility of automatic emotional information retrieval from sound events and, on the other hand, the need for deeper understanding of the significance of the sound events’ semantic co...

Evolutionary music composition is a prominent technique for automatic music generation. The immense adaptation potential of evolutionary algorithms has allowed the realisation of systems that automatically produce music through feature and interactive-based composition approaches. Feature-based composition employs qualitatively descriptive music fe...

Conceptual blending is a powerful tool for computational creativity where, for example, the properties of two harmonic spaces may be combined in a consistent manner to produce a novel harmonic space. However, deciding about the importance of property features in the input spaces and evaluating the results of conceptual blending is a nontrivial task...

This paper presents two novel strategies for processing chroma vectors corresponding to polyphonic audio, and producing a symbolic representation known as GCT (General Chord Type). This corresponds to a fundamental step in the conversion of general polyphonic audio files to this symbolic representation, which is required for enlarging the current c...

Melodic harmonisation deals with the assignment of harmony (chords) over a given melody. Probabilistic approaches to melodic harmonisation utilise statistical information derived from a training dataset to harmonise a melody. This paper proposes a probabilistic approach for the automatic generation of voice leading for the bass note on a set of giv...

We present a computational framework for chord invention based on a cognitive-theoretic perspective on conceptual blending. The framework builds on algebraic specifications, and solves two musicological problems. It automatically finds transitions between chord progressions of different keys or idioms, and it substitutes chords in a chord progressi...

This research focuses on concept invention processes and suggests that structural blending is a powerful mechanism that gives rise to novel musical concepts. Structural blending is omnipresent across several formal musical levels, from individual pieces harmoniously combining music characteristics of different pieces/styles, to entire musical style...

Conceptual blending is a cognitive theory whereby elements from diverse, but structurally-related, mental spaces are 'blended' giving rise to new conceptual spaces. This study focuses on structural blending utilising an algorith-mic formalisation for conceptual blending applied to harmonic concepts. More specifically, it investigates the ability of...

Probabilistic methodologies provide successful tools for automated music composition, such as melodic harmoni-sation, since they capture statistical rules of the music idioms they are trained with. Proposed methodologies focus either on specific aspects of harmony (e.g., generating abstract chord symbols) or incorporate the determination of many ha...

The General Chord Type (GCT) representation is appropriate for encoding tone simultaneities in any harmonic context (such as tonal, modal, jazz, octatonic, atonal). The GCT allows the rearrangement of the notes of a harmonic sonority such that abstract idiom-specific types of chords may be derived. This encoding is inspired by the standard roman nu...

With the advances of technology, multimedia tend to be a recurring and prominent component in almost all forms of communication. Although their content spans in various categories, there are two protuberant channels that are used for information conveyance, i.e. audio and visual. The former can transfer numerous content, ranging from low-level char...

Conceptual blending is a cognitive theory whereby elements from diverse, but structurally-related, mental spaces are " blended " giving rise to new conceptual spaces that often possess new powerful interpretative properties, allowing better understanding of known concepts or the emergence of novel concepts altogether. This paper provides an overvie...

In this paper we focus on issues of harmonic representa-tion and computational analysis. A new idiom-independent representation is proposed of chord types that is appropriate for encoding tone simultaneities in any harmonic context (such as tonal, modal, jazz, octatonic, atonal). The General Chord Type (GCT) representation, allows the re-arrangemen...

During the last decades, several methodologies have been proposed for the harmonization of a given melody with al-gorithmic means. Among the most successful are method-ologies that incorporate probabilistic mechanisms and sta-tistical learning, since they have the ability to generate har-monies that statistically adhere to the harmonic character-is...

In this work we aim to combine a game platform with the concept of collaborative music synthesis. We use bio- inspired intelligence for developing a world - the Lake - where multiple tribes of artificial, autonomous agents live within, having survival as their ultimate goal. The tribes exhibit primitive social swarm-based behavior and intelli- genc...

This paper examines a previously unstudied musical corpus de-rived from the polyphonic singing tradition of Epirus employing statistical methods. This analysis will mainly focus on unique harmonic aspects of these songs, which feature, for instance, unresolved dissonances (major second and minor seventh inter-vals) at structurally stable positions...

In this work we aim to combine a game platform with the concept of collaborative music synthesis. We use bioinspired intelligence for developing a world - the Lake - where multiple tribes of artificial, autonomous agents live within, having survival as their ultimate goal. The tribes exhibit primitive social swarm-based behavior and intelligence, w...

Analyzing and generating music material has been a field of intense research, combining scientific disciplines from computational intelligence and signal processing or computational music analysis. This chapter reviews the application of methods that utilize genetic programming (GP) along with other methods for tackling several tasks that pertain t...

Music is an amalgam of logic and emotion, order and dissonance, along with many combinations of contradicting notions which allude to deterministic chaos. Therefore, it comes as no surprise that several research works have examined the utilization of dynamical systems for symbolic music composition. The main motivation of the paper at hand is the a...

Drum rhythm automatic construction is an important step towards the design of systems which automatically compose music. This work describes a novel mechanism that allows a system, namely the evoDrummer, to create novel rhythms with reference to a base rhythm. The user interactively defines the amount of divergence between the base rhythm and the g...

Key changes are common in Western classical music. The precise segmentation of a music piece at instances where key changes occur allows for further analysis, like self-similarity analysis, chord recognition, and several other techniques that mainly pertain to the characterization of music content. This article examines the automatic segmentation o...

Automatic music composition is an enchanting field of research, inspiring both researchers and musicians. The implementation of systems that perform this task, incorporates an algorithmic part which makes decisions on which notes/sounds will be heard, when they will be heard, for how long and how loud. The intriguing part of automatic composition i...

Computational Intelligence encompasses tools that allow the fast convergence and adaptation to several problems, a fact that makes them eligible for real-time implementations. The paper at hand discusses the utilization of intelligent algorithms (i.e. Differential Evolution and Genetic Algorithms) for the creation of an adaptive system that is able...

Real--time transcription of drum signals is an emerging area of research. Several applications for music education and commercial use can utilize such algorithms and allow for an easy-to-use way to interpret drum signals in real--time. The paper at hand proposes a system that performs real--time drums transcription. The proposed system consists of...

Music composition from nonlinear dynamics has been a subject of thorough research, producing interesting music tracks. Simple chaotic maps or even more complex iterative schemes have been proposed, taking advantage of the "structured spontaneity" of nonlinear dynamics by directly transforming the mathematical objects to musical enti-ties. In this w...

Algorithmic music synthesis with intelligent method-ologies is a subject of research under both unsupervised and supervised forms, with the production of rhythm being an important aspect of the compositional process. Unsupervised algorithms tend to produce rhythms that are described either as simplistic and repetitive, or very complex and unstable....

Music composition with algorithms inspired by nature has led to the creation of systems that compose music with rich characteristics. However, the complexity imposed by un-supervised algorithms may arguably be considered as unde-sired, especially when considering the composition of rhythms. This work examines the composition of rhythms through L an...

Automatic music composition and sound syn-thesis is a field of study that gains continuously in-creasing attention. The introduction of Evolutionary Computation has further boosted the research towards exploring ways to incorporate human supervision and guidance in the automatic evolution of melodies and sounds. This kind of human–machine interacti...

Orchestration of computer-aided music composition aims to approximate musical expression using vertical instrument sound combinations, i.e. through finding appropriate sets of instruments to replicate synthesized sound samples. In this work, we focus on horizontal orchestration replication, i.e. the potential of replicating the instantaneous intens...

The efficient specification of aesthetic measures for music as a part of modelling human conception of sound is a challenging task and has motivated several research works. It is not only targeted to the creation of automatic music composers and raters, but also reinforces the research for a deeper understanding of human noesis. The aim of this wor...

Computer aided musical analysis has led a research stream to explore the description of an entire musical piece by a single value. Combinations of such values, often called global features, have been used for several identification tasks on pieces with symbolic music representation. In this work we extend some ideas that estimate information entrop...

Several approaches based on the ‘Markov chain model’ have been proposed to tackle the composer identification task. In the paper at hand, we propose to capture phrasing structural information from inter onset and pitch intervals of pairs of consecutive notes in a musical piece, by incorporating this information into a weighted variation of a first...

During the last decade many efforts for music information retrieval have been made utilizing Computational Intelligence methods. Here, we examine the information capacity of the Dodecaphonic Trace Vector for composer classification and identification. To this end, we utilize Probabilistic Neural Networks for the construction of a “similarity matrix...