Evolution of classifiers for pitch estimation of piano music using cartesian genetic programming

Pitch Estimation, also known as Fundamental Frequency (F0) estimation, has been a popular research topic for many years, and is still investigated nowadays. The goal of Pitch Estimation is to find the pitch or fundamental frequency of a digital recording of a speech or musical notes. It plays an important role, because it is the key to identify which notes are being played and at what time. Pitch Estimation of real instruments is a very hard task to address. Each instrument has its own physical characteristics, which reflects in different spectral characteristics. Furthermore, the recording conditions can vary from studio to studio and background noises must be considered. This dissertation presents a novel approach to the problem of Pitch Estimation, using Cartesian Genetic Programming (CGP).We take advantage of evolutionary algorithms, in particular CGP, to explore and evolve complex mathematical functions that act as classifiers. These classifiers are used to identify piano notes pitches in an audio signal. To help us with the codification of the problem, we built a highly flexible CGP Toolbox, generic enough to encode different kind of programs. The encoded evolutionary algorithm is the one known as 1 + , and we can choose the value for . The toolbox is very simple to use. Settings such as the mutation probability, number of runs and generations are configurable. The cartesian representation of CGP can take multiple forms and it is able to encode function parameters. It is prepared to handle with different type of fitness functions: minimization of f(x) and maximization of f(x) and has a useful system of callbacks. We trained 61 classifiers corresponding to 61 piano notes. A training set of audio signals was used for each of the classifiers: half were signals with the same pitch as the classifier (true positive signals) and the other half were signals with different pitches (true negative signals). F-measure was used for the fitness function. Signals with the same pitch of the classifier that were correctly identified by the classifier, count as a true positives. Signals with the same pitch of the classifier that were not correctly identified by the classifier, count as a false negatives. Signals with different pitch of the classifier that were not identified by the classifier, count as a true negatives. Signals with different pitch of the classifier that were identified by the classifier, count as a false positives. Our first approach was to evolve classifiers for identifying artifical signals, created by mathematical functions: sine, sawtooth and square waves. Our function set is basically composed by filtering operations on vectors and by arithmetic operations with constants and vectors. All the classifiers correctly identified true positive signals and did not identify true negative signals. We then moved to real audio recordings. For testing the classifiers, we picked different audio signals from the ones used during the training phase. For a first approach, the obtained results were very promising, but could be improved. We have made slight changes to our approach and the number of false positives reduced 33%, compared to the first approach. We then applied the evolved classifiers to polyphonic audio signals, and the results indicate that our approach is a good starting point for addressing the problem of Pitch Estimation.

Pathfinder. Performance at the Sonorities Festival of Contemporary Music 2016

Pathfinder (2016) is an audiovisual performance-game for a solo drummer,exploring the synergies between multiple contemporary creative practices.The work navigates between music composition, improvisation, projection/ light art and game art. At its heart lies a bespoke electro-acoustic instrument,the augmented drum-kit, used not only to provide the sonic content of the work in real-time, but also as a highly expressive game controller that interacts with an instrument-specific game. The musical instrument offers a much wider range of expressive possibilities, control and tactile feedback in comparison to a traditional general-purpose game controller, and as a result it affords a very diverse and nuanced gameplay performance. Live electronics, lights, projections and the drum-kit all make up the performance-game’s universe, within which the performer has to explore, adjust, navigate and complete a journey.

Neonatal palliative care attitude scale : development of an instrument to measure the barriers to and facilitators of palliative care in neonatal nursing

OBJECTIVE The aim of this research project was to obtain an understanding of the barriers to and facilitators of providing palliative care in neonatal nursing. This article reports the first phase of this research: to develop and administer an instrument to measure the attitudes of neonatal nurses to palliative care. METHODS The instrument developed for this research (the Neonatal Palliative Care Attitude Scale) underwent face and content validity testing with an expert panel and was pilot tested to establish temporal stability. It was then administered to a population sample of 1285 neonatal nurses in Australian NICUs, with a response rate of 50% (N 645). Exploratory factor-analysis techniques were conducted to identify scales and subscales of the instrument. RESULTS Data-reduction techniques using principal components analysis were used. Using the criteria of eigenvalues being 1, the items in the Neonatal Palliative Care Attitude Scale extracted 6 factors, which accounted for 48.1% of the variance among the items. By further examining the questions within each factor and the Cronbach’s of items loading on each factor, factors were accepted or rejected. This resulted in acceptance of 3 factors indicating the barriers to and facilitators of palliative care practice. The constructs represented by these factors indicated barriers to and facilitators of palliative care practice relating to (1) the organization in which the nurse practices, (2) the available resources to support a palliative model of care, and (3) the technological imperatives and parental demands. CONCLUSIONS The subscales identified by this analysis identified items that measured both barriers to and facilitators of palliative care practice in neonatal nursing. While establishing preliminary reliability of the instrument by using exploratory factor-analysis techniques, further testing of this instrument with different samples of neonatal nurses is necessary using a confirmatory factor-analysis approach.

Music purchase behaviour : the effect of emotional loyalty on intention to purchase.

This paper explores the influence of emotional loyalty on music purchase behaviour. Specifically, it examines whether emotional attachment to an artist's music influences loyalty to that artist, and how emotional loyalty influences a consumer's decision to purchase music. Data collection involved fifteen semi-structured interviews with young (18-30) subjects recruited through non-probability convenience sampling. Findings show that consumers who are emotionally loyal to an artistes) are more inclined to purchase the music rather than download free of charge.

Technical support and professional development : using remote desktops to address bottlenecks in music technology

This paper presents research findings about the use of remote desktop applications to teach music sequencing software. It highlights the successes, shortcomings and interactive issues encountered during a pilot project with a theoretical focus on a specific interactive bottleneck. The paper proposes a new delivery and partnership model to widen this bottleneck, which currently hinders interactions between the technical support, education and professional development communities in music technology.