Concatenative Synthesis for Novel Timbral Creation

Modern day musicians rely on a variety of instruments for musical expression. Tones produced from electronic instruments have become almost as commonplace as those produced by traditional ones as evidenced by the plethora of artists who can be found composing and performing with nothing more than a personal computer. This desire to embrace technical innovation as a means to augment performance art has created a budding field in computer science that explores the creation and manipulation of sound for artistic purposes. One facet of this new frontier concerns timbral creation, or the development of new sounds with unique characteristics that can be wielded by the musician as a virtual instrument. This thesis presents Timcat, a software system that can be used to create novel timbres from prerecorded audio. Various techniques for timbral feature extraction from short audio clips, or grains, are evaluated for use in timbral feature spaces. Clustering is performed on feature vectors in these spaces and groupings are recombined using concatenative synthesis techniques in order to form new instrument patches. The results reveal that interesting timbres can be created using features extracted by both newly developed and existing signal analysis techniques, many common in other fields though not often applied to music audio signals. Several of the features employed also show high accuracy for instrument separation in randomly mixed tracks. Survey results demonstrate positive feedback concerning the timbres created by Timcat from electronic music composers, musicians, and music lovers alike

Ontology of music performance variation

Performance variation in rhythm determines the extent that humans perceive and feel the effect of rhythmic pulsation and music in general. In many cases, these rhythmic variations can be linked to percussive performance. Such percussive performance variations are often absent in current percussive rhythmic models. The purpose of this thesis is to present an interactive computer model, called the PD-103, that simulates the micro-variations in human percussive performance. This thesis makes three main contributions to existing knowledge: firstly, by formalising a new method for modelling percussive performance; secondly, by developing a new compositional software tool called the PD-103 that models human percussive performance, and finally, by creating a portfolio of different musical styles to demonstrate the capabilities of the software. A large database of recorded samples are classified into zones based upon the vibrational characteristics of the instruments, to model timbral variation in human percussive performance. The degree of timbral variation is governed by principles of biomechanics and human percussive performance. A fuzzy logic algorithm is applied to analyse current and first-order sample selection in order to formulate an ontological description of music performance variation. Asynchrony values were extracted from recorded performances of three different performance skill levels to create \timing fingerprints" which characterise unique features to each percussionist. The PD-103 uses real performance timing data to determine asynchrony values for each synthesised note. The spectral content of the sample database forms a three-dimensional loudness/timbre space, intersecting instrumental behaviour with music composition. The reparameterisation of the sample database, following the analysis of loudness, spectral flatness, and spectral centroid, provides an opportunity to explore the timbral variations inherent in percussion instruments, to creatively explore dimensions of timbre. The PD-103 was used to create a music portfolio exploring different rhythmic possibilities with a focus on meso-periodic rhythms common to parts of West Africa, jazz drumming, and electroacoustic music. The portfolio also includes new timbral percussive works based on spectral features and demonstrates the central aim of this thesis, which is the creation of a new compositional software tool that integrates human percussive performance and subsequently extends this model to different genres of music

Assessing Music Perception in Young Children: Evidence for and Psychometric Features of the M-Factor

Given the relationship between language acquisition and music processing, musical perception (MP) skills have been proposed as a tool for early diagnosis of speech and language difficulties; therefore, a psychometric instrument is needed to assess music perception in children under 10 years of age, a crucial period in neurodevelopment. We created a set of 80 musical stimuli encompassing seven domains of music perception to inform perception of tonal, atonal, and modal stimuli, in a random sample of 1006 children, 6–13 years of age, equally distributed from first to fifth grades, from 14 schools (38% private schools) in So Paulo State. The underlying model was tested using confirmatory factor analysis. A model encompassing seven orthogonal specific domains (contour, loudness, scale, timbre, duration, pitch, and meter) and one general music perception factor, the “m-factor,” showed excellent fit indices. The m-factor, previously hypothesized in the literature but never formally tested, explains 93% of the reliable variance in measurement, while only 3.9% of the reliable variance could be attributed to the multidimensionality caused by the specific domains. The 80 items showed no differential item functioning based on sex, age, or enrolment in public vs. private school, demonstrating the important psychometric feature of invariance. Like Charles Spearman's g-factor of intelligence, the m-factor is robust and reliable. It provides a convenient measure of auditory stimulus apprehension that does not rely on verbal information, offering a new opportunity to probe biological and psychological relationships with music perception phenomena and the etiologies of speech and language disorders

The Consensual Assessment Technique as a measure of creativity in children\u27s musical compositions motivated by visual and verbal stimuli

ABSTRACT The purposes of this study were: 1) To compare the relationship between the degrees of creativity shown in musical compositions of third grade students (N=163) when they were exposed to either a visual or verbal stimulus, and 2) to examine inter-judge reliability for creativity ratings using the Consensual Assessment Technique (CAT) with instrumental group compositions. Throughout a nine-week teaching unit, all subjects participated in regular music classes where they learned compositional techniques and concepts. They worked in small cooperative learning groups of 3 to 6 students throughout the unit to compose several “mini” compositions and two large-scale compositions. For the last composition, four classes received a verbal stimulus and the other four received a visual artwork stimulus. Performances of these 34 compositions were videotaped and judged on 13 dimensions by three elementary music teachers using the CAT. Even though both stimuli were successful compositional motivators for their respective groups, the subtle differences in stimuli types over a short period of time as in this study were not influential enough to affect the creativity scores of student compositions. No significant differences were found between the two groups for any of the dimensions. Reliability scores were calculated, and ranged from .48 to .83 with coefficients on 11 of the 13 dimensions resulting in significant (p\u3c.05) agreements among the three judges. This assessment technique was found to be successful when used with small group instrumental music compositions of third grade students

Automatic sound synthesizer programming: techniques and applications

The aim of this thesis is to investigate techniques for, and applications of automatic sound synthesizer programming. An automatic sound synthesizer programmer is a system which removes the requirement to explicitly specify parameter settings for a sound synthesis algorithm from the user. Two forms of these systems are discussed in this thesis: tone matching programmers and synthesis space explorers. A tone matching programmer takes at its input a sound synthesis algorithm and a desired target sound. At its output it produces a configuration for the sound synthesis algorithm which causes it to emit a similar sound to the target. The techniques for achieving this that are investigated are genetic algorithms, neural networks, hill climbers and data driven approaches. A synthesis space explorer provides a user with a representation of the space of possible sounds that a synthesizer can produce and allows them to interactively explore this space. The applications of automatic sound synthesizer programming that are investigated include studio tools, an autonomous musical agent and a self-reprogramming drum machine. The research employs several methodologies: the development of novel software frameworks and tools, the examination of existing software at the source code and performance levels and user trials of the tools and software. The main contributions made are: a method for visualisation of sound synthesis space and low dimensional control of sound synthesizers; a general purpose framework for the deployment and testing of sound synthesis and optimisation algorithms in the SuperCollider language sclang; a comparison of a variety of optimisation techniques for sound synthesizer programming; an analysis of sound synthesizer error surfaces; a general purpose sound synthesizer programmer compatible with industry standard tools; an automatic improviser which passes a loose equivalent of the Turing test for Jazz musicians, i.e. being half of a man-machine duet which was rated as one of the best sessions of 2009 on the BBC's 'Jazz on 3' programme

Vocal imitation for query by vocalisation

PhD ThesisThe human voice presents a rich and powerful medium for expressing sonic ideas such as musical sounds. This capability extends beyond the sounds used in speech, evidenced for example in the art form of beatboxing, and recent studies highlighting the utility of vocal imitation for communicating sonic concepts. Meanwhile, the advance of digital audio has resulted in huge libraries of sounds at the disposal of music producers and sound designers. This presents a compelling search problem: with larger search spaces, the task of navigating sound libraries has become increasingly difficult. The versatility and expressive nature of the voice provides a seemingly ideal medium for querying sound libraries, raising the question of how well humans are able to vocally imitate musical sounds, and how we might use the voice as a tool for search. In this thesis we address these questions by investigating the ability of musicians to vocalise synthesised and percussive sounds, and evaluate the suitability of different audio features for predicting the perceptual similarity between vocal imitations and imitated sounds. In the first experiment, musicians were tasked with imitating synthesised sounds with one or two time–varying feature envelopes applied. The results show that participants were able to imitate pitch, loudness, and spectral centroid features accurately, and that imitation accuracy was generally preserved when the imitated stimuli combined two, non-necessarily congruent features. This demonstrates the viability of using the voice as a natural means of expressing time series of two features simultaneously. The second experiment consisted of two parts. In a vocal production task, musicians were asked to imitate drum sounds. Listeners were then asked to rate the similarity between the imitations and sounds from the same category (e.g. kick, snare etc.). The results show that drum sounds received the highest similarity ratings when rated against their imitations (as opposed to imitations of another sound), and overall more than half the imitated sounds were correctly identified with above chance accuracy from the imitations, although this varied considerably between drum categories. The findings from the vocal imitation experiments highlight the capacity of musicians to vocally imitate musical sounds, and some limitations of non– verbal vocal expression. Finally, we investigated the performance of different audio features as predictors of perceptual similarity between the imitations and imitated sounds from the second experiment. We show that features learned using convolutional auto–encoders outperform a number of popular heuristic features for this task, and that preservation of temporal information is more important than spectral resolution for differentiating between the vocal imitations and same–category drum sounds

Is Vivaldi smooth and takete? Non-verbal sensory scales for describing music qualities

Studies on the perception of music qualities (such as induced or perceived emotions, performance styles, or timbre nuances) make a large use of verbal descriptors. Although many authors noted that particular music qualities can hardly be described by means of verbal labels, few studies have tried alternatives. This paper aims at exploring the use of non-verbal sensory scales, in order to represent different perceived qualities in Western classical music. Musically trained and untrained listeners were required to listen to six musical excerpts in major key and to evaluate them from a sensorial and semantic point of view (Experiment 1). The same design (Experiment 2) was conducted using musically trained and untrained listeners who were required to listen to six musical excerpts in minor key. The overall findings indicate that subjects\u2019 ratings on non-verbal sensory scales are consistent throughout and the results support the hypothesis that sensory scales can convey some specific sensations that cannot be described verbally, offering interesting insights to deepen our knowledge on the relationship between music and other sensorial experiences. Such research can foster interesting applications in the field of music information retrieval and timbre spaces explorations together with experiments applied to different musical cultures and contexts

A Multifaceted Performance Model for the Multiple Percussion Performance Practice: Performance Analysis of Select Works toward Developing a Graduate Curriculum

The purpose of this document is to articulate the various dimensions of the solo multiple percussion performance practice, the primary objective being to construct appropriate graduate curricula. It was found that the necessary skills and concepts could be categorized into four dimensions that make up the multi-faceted model: (1) equipment and setup, (2) notational style, (3) technical demands, and (4) conceptual performance. Requisite skills were posited from performance analyses of over fifty solo works that range from intermediate to advanced difficulty. Representative works are described that might effectively introduce and challenge these requisite skills and concepts, as are exemplary pieces that require their mastery. One piece that I performed for recital within my doctoral program was selected for each dimension to provide experiential details: The Anvil Chorus is used to describe equipment and setup, Psappha for notational style and devices, Thirteen Drums for technical facility, and Tunnels for the performance concept. I conclude the document with sample program curricula suggested for master’s and doctoral level, as well as curricula specific to each dimension of the performance model. It is my hope that the percussion instructor will use this model to analyze their own inventory and to include future additions to the literature for creating an effective and comprehensive graduate multiple percussion curriculum

The development of corpus-based computer assisted composition program and its application for instrumental music composition

In the last 20 years, we have seen the nourishing environment for the development of music software using a corpus of audio data expanding significantly, namely that synthesis techniques producing electronic sounds, and supportive tools for creative activities are the driving forces to the growth. Some software produces a sequence of sounds by means of synthesizing a chunk of source audio data retrieved from an audio database according to a rule. Since the matching of sources is processed according to their descriptive features extracted by FFT analysis, the quality of the result is significantly influenced by the outcomes of the Audio Analysis, Segmentation, and Decomposition. Also, the synthesis process often requires a considerable amount of sample data and this can become an obstacle to establish easy, inexpensive, and user-friendly applications on various kinds of devices. Therefore, it is crucial to consider how to treat the data and construct an efficient database for the synthesis. We aim to apply corpusbased synthesis techniques to develop a Computer Assisted Composition program, and to investigate the actual application of the program on ensemble pieces. The goal of this research is to apply the program to the instrumental music composition, refine its function, and search new avenues for innovative compositional method