A musical performance renders an acoustic realization of a musical score or other representation of a composition. Different performances of the same composition may vary in terms of performance parameters such as timing or dynamics, and these variations may have a major impact on how a listener perceives the music. The analysis of music performance has traditionally been a peripheral topic for the MIR research community, where often a single audio recording is used as representative of a musical work. This paper surveys the field of Music Performance Analysis (MPA) from several perspectives including the measurement of performance parameters, the relation of those parameters to the actions and intentions of a performer or perceptual effects on a listener, and finally the assessment of musical performance. This paper also discusses MPA as it relates to MIR, pointing out opportunities for collaboration and future research in both areas.

/pdf/an-interdisciplinary-review-of-music-performance-analysis-4pyavu4ho5.pdf

An Interdisciplinary Review of Music Performance Analysis

Music Information Retrieval (MIR) tends to focus on the analysis of audio signals. Often, a single music recording is used as representative of a "song" even though different performances of the same song may reveal different properties. A performance is distinct in many ways from a (arguably more abstract) representation of a "song," "piece," or musical score. The characteristics of the (recorded) performance -- as opposed to the score or musical idea -- can have a major impact on how a listener perceives music. The analysis of music performance, however, has been traditionally only a peripheral topic for the MIR research community. This paper surveys the field of Music Performance Analysis (MPA) from various perspectives, discusses its significance to the field of MIR, and points out opportunities for future research in this field.

Music Performance Analysis: A Survey

Vibrato and portamento constitute two expressive devices involving continuous pitch modulation and is widely employed in string, voice, wind music instrument performance. Automatic extraction and analysis of such expressive features form some of the most important aspects of music performance research and represents an under-explored area in music information retrieval. This thesis aims to provide computational and scalable solutions for the automatic extraction and analysis of performed vibratos and portamenti. Applications of the technologies include music learning, musicological analysis, music information retrieval (summarisation, similarity assessment), and music expression synthesis. To automatically detect vibratos and estimate their parameters, we propose a novel method based on the Filter Diagonalisation Method (FDM). The FDM remains robust over short time frames, allowing frame sizes to be set at values small enough to accurately identify local vibrato characteristics and pinpoint vibrato boundaries. For the determining of vibrato presence, we test two alternate decision mechanisms—the Decision Tree and Bayes’ Rule. The FDM systems are compared to state-of-the-art techniques and obtains the best results. The FDM’s vibrato rate accuracies are above 92.5%, and the vibrato extent accuracies are about 85%. We use the Hidden Markov Model (HMM) with Gaussian Mixture Model (GMM) to detect portamento existence. Upon extracting the portamenti, we propose a Logistic Model for describing portamento parameters. The Logistic Model has the lowest root mean squared error and the highest adjusted Rsquared value comparing to regression models employing Polynomial and Gaussian functions, and the Fourier Series. The vibrato and portamento detection and analysis methods are implemented in AVA, an interactive tool for automated detection, analysis, and visualisation of vibrato and portamento. Using the system, we perform crosscultural analyses of vibrato and portamento differences between erhu and violin performance styles, and between typical male or female roles in Beijing opera singing. Statement of Originality I, Luwei Yang, confirm that the research included within this thesis is my own work or that where it has been carried out in collaboration with, or supported by others, that this is duly acknowledged below and my contribution indicated. Previously published material is also acknowledged below. I attest that I have exercised reasonable care to ensure that the work is original, and does not to the best of my knowledge break any UK law, infringe any third party’s copyright or other Intellectual Property Right, or contain any confidential material. I accept that the College has the right to use plagiarism detection software to check the electronic version of the thesis. I confirm that this thesis has not been previously submitted for the award of a degree by this or any other university. The copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the author. Signature: Luwei Yang Date: 19 September 2016

Computational modelling and analysis of vibrato and portamento in expressive music performance

Electroacoustic music: analytical perspectives

/pdf/an-interdisciplinary-review-of-music-performance-analysis-4yg0p9v9zd.pdf

Despite a large literature in Quality of Service (QoS) evaluation, end-user QoS provisioning remains an open research field. There is no general agreement about what to measure and how to do it in order to ensure real quality levels. Even more, new heterogeneous multimedia applications have redefined the problem, turning many previous implementations no longer appropriate for current scenario.This paper addresses the problem of QoS assessment of a multimedia service over IP as perceived by humans, applying statistical learning techniques. We describe two end-to-end performance evaluation methodologies, the former based on Perceived QoS (PQoS) and the latter based on functional nonparametric regression. By merging them we build an improved system for end-to-end PQoS evaluation which allows analysing and better understanding the tradeoffs between different proposed techniques in the field.

/pdf/a-user-perspective-for-end-to-end-quality-of-service-26pht9z863.pdf

A user perspective for end-to-end quality of service evaluation in multimedia networks

In the Electrical Engineering degree, the integration of theoretical and practical knowledge is essential. Throughout the degree, there must be instances where the students can face specific problems and test their learning. With this in mind, an integrative workshop is implemented in the third year that seeks to strengthen skills such as: analysis and design of signal conditioning circuits, designing and printing circuits, signal acquisition and processing, pattern recognition and classification, integration of a system. The problem of the identification of household appliances from consumption records presents multiple challenges suitable to develop all the desired skills and also for the initiation to research.

https://dialnet.unirioja.es/descarga/articulo/7919862.pdf

Household Appliances Identification: An integrative workshop for the Electrical Engineering degree

This work deals with pitch content visualization tools for the analysis of music performance from audio recordings. An existing computational method for the representation of pitch contours is briefly reviewed. Its application to music analysis is exemplified with two pieces of non-notated music: a field recording of a folkloric form of polyphonic singing and a commercial recording by a noted blues musician. Both examples have vocal parts exhibiting complex pitch evolution, difficult to analyze and notate with precision using Western common music notation. By using novel time-frequency analysis techniques that improve the location of the components of a harmonic sound, the melodic content representation implemented here allows a detailed study of aspects related to pitch intonation and tuning. This in turn permits an objective measurement of essential musical characteristics that are difficult or impossible to properly evaluate by subjective perception alone, and which are often not accounted for in traditional musicological analysis. Two software tools are released that allow the practical use of the described methods.

/pdf/pitch-content-visualization-tools-for-music-performance-2mjbyamgl2.pdf

Pitch content visualization tools for music performance analysis

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A user perspective for end-to-end quality of service evaluation in multimedia networks

Household Appliances Identification: An integrative workshop for the Electrical Engineering degree

Pitch content visualization tools for music performance analysis