A constraint-based framework to model harmony for algorithmic composition

Music constraint systems provide a rule-based approach to composition. Existing systems allow users to constrain the harmony, but the constrainable harmonic information is restricted to pitches and intervals between pitches. More abstract analytical information such as chord or scale types, their root, scale degrees, enharmonic note representations, whether a note is the third or fifth of a chord and so forth are not supported. However, such information is important for modelling various music theories. This research proposes a framework for modelling harmony at a high level of abstraction. It explicitly represents various analytical information to allow for complex theories of harmony. It is designed for efficient propagation-based constraint solvers. The framework supports the common 12-tone equal temperament, and arbitrary other equal temperaments. Users develop harmony models by applying user-defined constraints to its music representation. Three examples demonstrate the expressive power of the framework: (1) an automatic melody harmonisation with a simple harmony model; (2) a more complex model implementing large parts of Schoenberg’s tonal theory of harmony; and (3) a composition in extended tonality. Schoenberg’s comprehensive theory of harmony has not been computationally modelled before, neither with constraints programming nor in any other way.

Algorithms for an Automatic Transcription of Live Music Performances into Symbolic Format

This paper addresses the problem of the real-time automatic transcription of a live music performance into a symbolic format. The source data are given by any music instrument or other device able to communicate through a performance protocol. During a performance, music events are parsed and their parameters are evaluated thanks to rhythm and pitch detection algorithms. The final step is the creation of a well-formed XML document, validated against the new international standard known as IEEE 1599. This work will shortly describe both the software environment and the XML format, but the main analysis will involve the real-time recognition of music events. Finally, a case study will be presented: PureMX, a set of Pure Data externals, able to perform the automatic transcription of MIDI events

PureMX: Automatic transcription of MIDI live music performances into XML format

This paper addresses the problem of the real-time automatic transcription of a live music performance into a symbolic format based on XML. The source data are given by any music instrument or other device able to communicate with Pure Data by MIDI. Pure Data is a free, multi-platform, real-time programming environment for graphical, audio, and video processing. During a performance, music events are parsed and their parameters are evaluated thanks to rhythm and pitch detection algorithms. The final step is the creation of a well-formed XML document, validated against the new international standard known as IEEE 1599. This work will shortly describe both the software environment and the XML format, but the main analysis will involve the realtime recognition of music events. Finally, a case study will be presented: PureMX, an application able to perform such an automatic transcription

Using Mathematical Research Methods to Solve a Problem in Music Theory Instruction, Specifically, the Teaching of Secondary Dominant Chords

The mathematical method for research is used to find a solution to a problem in music theory: understanding and identifying secondary dominant chords. By reviewing and assessing the teaching methods of university professors and theory textbooks, and comparing those findings with student reviews, a new method for teaching the concept is developed. The proposed system incorporates aural, visual, and kinetic exercises to serve every learner. The literature review and sample unit plan are followed by a possible procedure for testing the effectiveness of the new method

Harmony and Technology Enhanced Learning

New technologies offer rich opportunities to support education in harmony. In this chapter we consider theoretical perspectives and underlying principles behind technologies for learning and teaching harmony. Such perspectives help in matching existing and future technologies to educational purposes, and to inspire the creative re-appropriation of technologies

Machine Annotation of Traditional Irish Dance Music

The work presented in this thesis is validated in experiments using 130 realworld field recordings of traditional music from sessions, classes, concerts and commercial recordings. Test audio includes solo and ensemble playing on a variety of instruments recorded in real-world settings such as noisy public sessions. Results are reported using standard measures from the field of information retrieval (IR) including accuracy, error, precision and recall and the system is compared to alternative approaches for CBMIR common in the literature

Engraving Oriented Joint Estimation of Pitch Spelling and Local and Global Keys

We revisit the problems of pitch spelling and tonality guessing with a new algorithm for their joint estimation from a MIDI file including information about the measure boundaries. Our algorithm does not only identify a global key but also local ones all along the analyzed piece. It uses Dynamic Programming techniques to search for an optimal spelling in term, roughly, of the number of accidental symbols that would be displayed in the engraved score. The evaluation of this number is coupled with an estimation of the global key and some local keys, one for each measure. Each of the three informations is used for the estimation of the other, in a multi-steps procedure. An evaluation conducted on a monophonic and a piano dataset, comprising 216 464 notes in total, shows a high degree of accuracy, both for pitch spelling (99.5% on average on the Bach corpus and 98.2% on the whole dataset) and global key signature estimation (93.0% on average, 95.58% on the piano dataset). Designed originally as a backend tool in a music transcription framework, this method should also be useful in other tasks related to music notation processing.Comment: International Conference on Technologies for Music Notation and Representation (TENOR), Apr 2024, Zurich (CH), Switzerlan

On the analysis of musical performance by computer

Existing automatic methods of analysing musical performance can generally be described as music-oriented DSP analysis. However, this merely identifies attributes, or artefacts which can be found within the performance. This information, though invaluable, is not an analysis of the performance process. The process of performance first involves an analysis of the score (whether from a printed sheet or from memory), and through this analysis, the performer decides how to perform the piece. Thus, an analysis of the performance process requires an analysis of the performance attributes and artefacts in the context of the musical score. With this type analysis it is possible to ask profound questions such as “why or when does a performer use this technique”. The work presented in this thesis provides the tools which are required to investigate these performance issues. A new computer representation, Performance Markup Language (PML) is presented which combines the domains of the musical score, performance information and analytical structures. This representation provides the framework with which information within these domains can be cross-referenced internally, and the markup of information in external files. Most importantly, the rep resentation defines the relationship between performance events and the corresponding objects within the score, thus facilitating analysis of performance information in the context of the score and analyses of the score. To evaluate the correspondences between performance notes and notes within the score, the performance must be analysed using a score-performance matching algorithm. A new score-performance matching algorithm is presented in this document which is based on Dynamic Programming. In score-performance matching there are situations where dynamic programming alone is not sufficient to accurately identify correspondences. The algorithm presented here makes use of analyses of both the score and the performance to overcome the inherent shortcomings of the DP method and to improve the accuracy and robustness of DP matching in the presence of performance errors and expressive timing. Together with the musical score and performance markup, the correspondences identified by the matching algorithm provide the minimum information required to investigate musical performance, and forms the foundation of a PML representation. The Microtonalism project investigated the issues surrounding the performance of microtonal music on conventional (i.e. non microtonal specific) instruments, namely voice. This included the automatic analysis of vocal performances to extract information regarding pitch accuracy. This was possible using tools developed using the performance representation and the matching algorithm