Exploring probabilistic grammars of symbolic music using PRISM

In this paper we describe how we used the logic-based probabilistic programming language PRISM to conduct a systematic comparison of several probabilistic models of symbolic music, including 0th and 1st order Markov models over pitches and intervals, and a probabilistic grammar with two parameterisations. Using PRISM allows us to take advantage of variational Bayesian methods for assessing the goodness of fit of the models. When applied to a corpus of Bach chorales and the Essen folk song collection, we found that, depending on various parameters, the probabilistic grammars sometimes but not always out-perform the simple Markov models. Examining how the models perform on smaller subsets of pieces, we find that the simpler Markov models do out-perform the best grammar-based model at the small end of the scale

Support for Learning Synthesiser Programming

When learning an instrument, students often like to emulate the sound and style of their favourite performers. The learning process takes many years of study and practice. In the case of synthesisers the vast parameter space involved can be daunting and unintuitive to the novice making it hard to define their desired sound and difficult to understand how it was achieved. Previous research has produced methods for automatically determining an appropriate parameter set to produce a desired sound but this can still require many parameters and does not explain or demonstrate the effect of particular parameters on the resulting sound. As a first step to solving this problem, this paper presents a new approach to searching the synthesiser parameter space to find a sound, reformulating it as a multi-objective optimisation problem (MOOP) where two competing objectives (closeness of perceived sonic match and number of parameters) are considered. As a proof-of-concept a pareto-optimal search algorithm (NSGA-II) is applied to CSound patches of varying complexity to generate a pareto-front of non-dominating (i.e. ”equally good”) solutions. The results offer insight into the extent to which the size and nature of parameter sets can be reduced whilst still retaining an acceptable degree of perceived sonic match between target and candidate sound

Form-Aware, Real-Time Adaptive Music Generation for Interactive Experiences

Many experiences offered to the public through interactive theatre, theme parks, video games, and virtual environments use music to complement the participants’ activity. There is a range of approaches to this, from straightforward playback of ‘stings’, to looped phrases, to on-the-fly note generation. Within the latter, traditional genres and forms are often not represented, with the music instead being typically loose in form and structure. We present work in progress on a new method for realtime music generation that can preserve traditional musical genres whilst being reactive in form to the activities of participants. The results of simulating participant trajectories and the effect this has on the music generation algorithms are presented, showing that the approach can successfully handle variable length forms whilst remaining substantially within the given musical style

Ethical Mining – A Case Study on MSR Mining Challenges

Research in Mining Software Repositories (MSR) is research involving human subjects, as the repositories usually contain data about developers’ interactions with the repositories. Therefore, any research in the area needs to consider the ethics implications of the intended activity before starting. This paper presents a discussion of the ethics implications of MSR research, using the mining challenges from the years 2010 to 2019 as a case study to identify the kinds of data used. It highlights problems that one may encounter in creating such datasets, and discusses ethics challenges that may be encountered when using existing datasets, based on a contemporary research ethics framework. We suggest that the MSR community should increase awareness of ethics issues by openly discussing ethics considerations in published articles

Ethics in the mining of software repositories

Research in Mining Software Repositories (MSR) is research involving human subjects, as the repositories usually contain data about developers’ and users’ interactions with the repositories and with each other. The ethics issues raised by such research therefore need to be considered before beginning. This paper presents a discussion of ethics issues that can arise in MSR research, using the mining challenges from the years 2006 to 2021 as a case study to identify the kinds of data used. On the basis of contemporary research ethics frameworks we discuss ethics challenges that may be encountered in creating and using repositories and associated datasets. We also report some results from a small community survey of approaches to ethics in MSR research. In addition, we present four case studies illustrating typical ethics issues one encounters in projects and how ethics considerations can shape projects before they commence. Based on our experience, we present some guidelines and practices that can help in considering potential ethics issues and reducing risks

A Framework to Evaluate the Adoption Potential of Interactive Performance Systems for Popular Music

Popular music plays a central role in the lives of millions of people. It motivates beginners, engages experienced musicians, and plays both functional (e.g. churches) and non-functional (e.g. music festivals) roles in many contexts. Forming and maintaining a popular music ensemble can be challenging, particularly for part-time musicians who face other demands on their time. Where an ensemble has a functional role, performing music of consistent style and quality becomes imperative yet the demands of everyday life mean that it is not always possible to have a full complement of musicians. Interactive music technology has the potential to substitute for absent musicians to give a consistent musical output. However, the technology to achieve this (for popular music) is not yet mature, or in a suitable form for adoption and use by musicians who are not experienced with interactive music systems, or who are unprepared to work in experimental music or with experimental systems (a particular concern for functional ensembles). This paper proposes a framework of issues to be considered when developing interactive music technologies for popular music ensemble performance. It explores aspects that are complementary to technological concerns, focusing on adoption and practice to guide future technological developments

Comparing models of symbolic music using probabilistic grammars and probabilistic programming

We conduct a systematic comparison of several probabilistic models of symbolic music, including zeroth and first order Markov models over pitches and intervals, a hidden Markov model over pitches, and a probabilistic context free grammar with two parameterisations, all implemented uniformly using a probabilistic programming language (PRISM). This allows us to take advantage of variational Bayesian methods for learning parameters and assessing the goodness of fit of the models in a principled way. When applied to a corpus of Bach chorales and the Essen folk song collection, we show that, depending on various parameters, the probabilistic grammars sometimes but not always out-perform the simple Markov models. On looking for evidence of over- fitting of complex models to small datasets, we find that even the smallest dataset is sufficient to support the richest parameterisation of the probabilistic grammars. However, examining how the models perform on smaller subsets of pieces, we find that the simpler Markov models do indeed out-perform the best grammar-based model at the small end of the scale

Lessons Learned in Exploring the Leap Motion™ Sensor for Gesture-based Instrument Design

The Leap Motion™ sensor offers fine-grained gesture-recognition and hand tracking. Since its release, there have been several uses of the device for instrument design, musical interaction and expression control, documented through online video. However, there has been little formal documented investigation of the potential and challenges of the platform in this context. This paper presents lessons learned from work-in-progress on the development of musical instruments and control applications using the Leap Motion™ sensor. Two instruments are presented: Air-Keys and Air-Pads and the potential for augmentation of a traditional keyboard is explored. The results show that the platform is promising in this context but requires various challenges, both physical and logical, to be overcome

A Reference Architecture and Score Representation for Popular Music Human-Computer Music Performance Systems

Popular music (characterized by improvised instrumental parts, beat and measure-level organization, and steady tempo) poses challenges for human-computer music performance (HCMP). Pieces of music are typically rearrangeable on-the-fly and involve a high degree of variation from ensemble to ensemble, and even between rehearsal and performance. Computer systems aiming to participate in such ensembles must therefore cope with a dynamic high-level structure in addition to the more traditional problems of beat-tracking, score-following, and machine improvisation. There are many approaches to integrating the components required to implement dynamic human-computer music performance systems. This paper presents a reference architecture designed to allow the typical sub-components (e.g. beat-tracking, tempo prediction, improvisation) to be integrated in a consistent way, allowing them to be combined and/or compared systematically. In addition, the paper presents a dynamic score representation particularly suited to the demands of popular music performance by computer