Algorithmic Compositional Methods and their Role in Genesis: A Multi-Functional Real-Time Computer Music System

Algorithmic procedures have been applied in computer music systems to generate compositional products using conventional musical formalism, extensions of such musical formalism and extra-musical disciplines such as mathematical models. This research investigates the applicability of such algorithmic methodologies for real-time musical composition, culminating in Genesis, a multi-functional real-time computer music system written for Mac OS X in the SuperCollider object-oriented programming language, and contained in the accompanying DVD. Through an extensive graphical user interface, Genesis offers musicians the opportunity to explore the application of the sonic features of real-time sound-objects to designated generative processes via different models of interaction such as unsupervised musical composition by Genesis and networked control of external Genesis instances. As a result of the applied interactive, generative and analytical methods, Genesis forms a unique compositional process, with a compositional product that reflects the character of its interactions between the sonic features of real-time sound-objects and its selected algorithmic procedures. Within this thesis, the technologies involved in algorithmic methodologies used for compositional processes, and the concepts that define their constructs are described, with consequent detailing of their selection and application in Genesis, with audio examples of algorithmic compositional methods demonstrated on the accompanying DVD. To demonstrate the real-time compositional abilities of Genesis, free explorations with instrumentalists, along with studio recordings of the compositional processes available in Genesis are presented in audiovisual examples contained in the accompanying DVD. The evaluation of the Genesis system’s capability to form a real-time compositional process, thereby maintaining real-time interaction between the sonic features of real-time sound objects and its selected algorithmic compositional methods, focuses on existing evaluation techniques founded in HCI and the qualitative issues such evaluation methods present. In terms of the compositional products generated by Genesis, the challenges in quantifying and qualifying its compositional outputs are identified, demonstrating the intricacies of assessing generative methods of compositional processes, and their impact on a resulting compositional product. The thesis concludes by considering further advances and applications of Genesis, and inviting further dissemination of the Genesis system and promotion of research into evaluative methods of generative techniques, with the hope that this may provide additional insight into the relative success of products generated by real-time algorithmic compositional processes

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

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

Automatic Transcription of Bass Guitar Tracks applied for Music Genre Classification and Sound Synthesis

Musiksignale bestehen in der Regel aus einer Überlagerung mehrerer Einzelinstrumente. Die meisten existierenden Algorithmen zur automatischen Transkription und Analyse von Musikaufnahmen im Forschungsfeld des Music Information Retrieval (MIR) versuchen, semantische Information direkt aus diesen gemischten Signalen zu extrahieren. In den letzten Jahren wurde häufig beobachtet, dass die Leistungsfähigkeit dieser Algorithmen durch die Signalüberlagerungen und den daraus resultierenden Informationsverlust generell limitiert ist. Ein möglicher Lösungsansatz besteht darin, mittels Verfahren der Quellentrennung die beteiligten Instrumente vor der Analyse klanglich zu isolieren. Die Leistungsfähigkeit dieser Algorithmen ist zum aktuellen Stand der Technik jedoch nicht immer ausreichend, um eine sehr gute Trennung der Einzelquellen zu ermöglichen. In dieser Arbeit werden daher ausschließlich isolierte Instrumentalaufnahmen untersucht, die klanglich nicht von anderen Instrumenten überlagert sind. Exemplarisch werden anhand der elektrischen Bassgitarre auf die Klangerzeugung dieses Instrumentes hin spezialisierte Analyse- und Klangsynthesealgorithmen entwickelt und evaluiert.Im ersten Teil der vorliegenden Arbeit wird ein Algorithmus vorgestellt, der eine automatische Transkription von Bassgitarrenaufnahmen durchführt. Dabei wird das Audiosignal durch verschiedene Klangereignisse beschrieben, welche den gespielten Noten auf dem Instrument entsprechen. Neben den üblichen Notenparametern Anfang, Dauer, Lautstärke und Tonhöhe werden dabei auch instrumentenspezifische Parameter wie die verwendeten Spieltechniken sowie die Saiten- und Bundlage auf dem Instrument automatisch extrahiert. Evaluationsexperimente anhand zweier neu erstellter Audiodatensätze belegen, dass der vorgestellte Transkriptionsalgorithmus auf einem Datensatz von realistischen Bassgitarrenaufnahmen eine höhere Erkennungsgenauigkeit erreichen kann als drei existierende Algorithmen aus dem Stand der Technik. Die Schätzung der instrumentenspezifischen Parameter kann insbesondere für isolierte Einzelnoten mit einer hohen Güte durchgeführt werden.Im zweiten Teil der Arbeit wird untersucht, wie aus einer Notendarstellung typischer sich wieder- holender Basslinien auf das Musikgenre geschlossen werden kann. Dabei werden Audiomerkmale extrahiert, welche verschiedene tonale, rhythmische, und strukturelle Eigenschaften von Basslinien quantitativ beschreiben. Mit Hilfe eines neu erstellten Datensatzes von 520 typischen Basslinien aus 13 verschiedenen Musikgenres wurden drei verschiedene Ansätze für die automatische Genreklassifikation verglichen. Dabei zeigte sich, dass mit Hilfe eines regelbasierten Klassifikationsverfahrens nur Anhand der Analyse der Basslinie eines Musikstückes bereits eine mittlere Erkennungsrate von 64,8 % erreicht werden konnte.Die Re-synthese der originalen Bassspuren basierend auf den extrahierten Notenparametern wird im dritten Teil der Arbeit untersucht. Dabei wird ein neuer Audiosynthesealgorithmus vorgestellt, der basierend auf dem Prinzip des Physical Modeling verschiedene Aspekte der für die Bassgitarre charakteristische Klangerzeugung wie Saitenanregung, Dämpfung, Kollision zwischen Saite und Bund sowie dem Tonabnehmerverhalten nachbildet. Weiterhin wird ein parametrischerAudiokodierungsansatz diskutiert, der es erlaubt, Bassgitarrenspuren nur anhand der ermittel- ten notenweisen Parameter zu übertragen um sie auf Dekoderseite wieder zu resynthetisieren. Die Ergebnisse mehrerer Hötest belegen, dass der vorgeschlagene Synthesealgorithmus eine Re- Synthese von Bassgitarrenaufnahmen mit einer besseren Klangqualität ermöglicht als die Übertragung der Audiodaten mit existierenden Audiokodierungsverfahren, die auf sehr geringe Bitraten ein gestellt sind.Music recordings most often consist of multiple instrument signals, which overlap in time and frequency. In the field of Music Information Retrieval (MIR), existing algorithms for the automatic transcription and analysis of music recordings aim to extract semantic information from mixed audio signals. In the last years, it was frequently observed that the algorithm performance is limited due to the signal interference and the resulting loss of information. One common approach to solve this problem is to first apply source separation algorithms to isolate the present musical instrument signals before analyzing them individually. The performance of source separation algorithms strongly depends on the number of instruments as well as on the amount of spectral overlap.In this thesis, isolated instrumental tracks are analyzed in order to circumvent the challenges of source separation. Instead, the focus is on the development of instrument-centered signal processing algorithms for music transcription, musical analysis, as well as sound synthesis. The electric bass guitar is chosen as an example instrument. Its sound production principles are closely investigated and considered in the algorithmic design.In the first part of this thesis, an automatic music transcription algorithm for electric bass guitar recordings will be presented. The audio signal is interpreted as a sequence of sound events, which are described by various parameters. In addition to the conventionally used score-level parameters note onset, duration, loudness, and pitch, instrument-specific parameters such as the applied instrument playing techniques and the geometric position on the instrument fretboard will be extracted. Different evaluation experiments confirmed that the proposed transcription algorithm outperformed three state-of-the-art bass transcription algorithms for the transcription of realistic bass guitar recordings. The estimation of the instrument-level parameters works with high accuracy, in particular for isolated note samples.In the second part of the thesis, it will be investigated, whether the sole analysis of the bassline of a music piece allows to automatically classify its music genre. Different score-based audio features will be proposed that allow to quantify tonal, rhythmic, and structural properties of basslines. Based on a novel data set of 520 bassline transcriptions from 13 different music genres, three approaches for music genre classification were compared. A rule-based classification system could achieve a mean class accuracy of 64.8 % by only taking features into account that were extracted from the bassline of a music piece.The re-synthesis of a bass guitar recordings using the previously extracted note parameters will be studied in the third part of this thesis. Based on the physical modeling of string instruments, a novel sound synthesis algorithm tailored to the electric bass guitar will be presented. The algorithm mimics different aspects of the instrument’s sound production mechanism such as string excitement, string damping, string-fret collision, and the influence of the electro-magnetic pickup. Furthermore, a parametric audio coding approach will be discussed that allows to encode and transmit bass guitar tracks with a significantly smaller bit rate than conventional audio coding algorithms do. The results of different listening tests confirmed that a higher perceptual quality can be achieved if the original bass guitar recordings are encoded and re-synthesized using the proposed parametric audio codec instead of being encoded using conventional audio codecs at very low bit rate settings

Automatic speech feature extraction using a convolutional restricted boltzmann machine

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, in fulfillment of the requirements for the degree of Master of Science 2017Restricted Boltzmann Machines (RBMs) are a statistical learning concept that can be interpreted as Arti cial Neural Networks. They are capable of learning, in an unsupervised fashion, a set of features with which to describe a data set. Connected in series RBMs form a model called a Deep Belief Network (DBN), learning abstract feature combinations from lower layers. Convolutional RBMs (CRBMs) are a variation on the RBM architecture in which the learned features are kernels that are convolved across spatial portions of the input data to generate feature maps identifying if a feature is detected in a portion of the input data. Features extracted from speech audio data by a trained CRBM have recently been shown to compete with the state of the art for a number of speaker identi cation tasks. This project implements a similar CRBM architecture in order to verify previous work, as well as gain insight into Digital Signal Processing (DSP), Generative Graphical Models, unsupervised pre-training of Arti cial Neural Networks, and Machine Learning classi cation tasks. The CRBM architecture is trained on the TIMIT speech corpus and the learned features veri ed by using them to train a linear classi er on tasks such as speaker genetic sex classi cation and speaker identi cation. The implementation is quantitatively proven to successfully learn and extract a useful feature representation for the given classi cation tasksMT 201

An Interactive Music Synthesizer for Gait Training in Neurorehabilitation

(Abstract to follow

Evaluation of product sound design within the context of emotion design and emotional branding

Thesis (Master)--Izmir Institute of Technology, Industrial Design, Izmir, 2005Includes bibliographical references (leaves: 111-122)Text in English; Abstract: Turkish and Englishxi, 127 leavesThe main purpose of this thesis is to set out the relationships between the work of product designers and the perceptions of costumers regarding the acceptability of product sounds. Product design that provides aesthetic appeal, pleasure and satisfaction can greatly influence success of a product. Sound as a cognitive artifact, plays a significant role in the cognition of product interaction and in shaping its identity. This thesis will review emotion theories end their application to sound design and sound quality modeling, the measurement of emotional responses to sound, and the relationship between psycho-acoustical sound descriptions and emotions. In addition to that, affects of sounds to emotionally significant brands will be evaluated so as to examine marketing values. One of the main purposes of chapter 2 is to prove knowledge about psychoacoustics; as product sound quality is a basic understanding of the underlying psychoacoustics phenomena. Perception; particularly sound perception and its elements are described during chapter 2. Starting with the description of sound wave and how our hear works, sound perception and auditory sensation is reviewed in continuation. In chapter 3, product sound quality concept and its evaluation principles are reviewed. Thus, in order to understand the coupling between the acoustic perception and the product design; knowledge of general principles for product sound quality are required. Chapter 4 can be considered as two main sections. .How does emotion act as a delighter in product design?. is examined to better understand customer and user experiences impacting pleasure-ability in first section. In the second section, emotion is evaluated through sound design. A qualitative evaluation is done so as to examine cognition and emotion in sound perception. Chapter 5 leads subject through emotional branding. Sounds that carry the brand.s identity are evaluated within. Sound design is re-evaluated as marketing strategy and examined with several instances. Keywords: Product sound design, psychoacoustics, product sound quality, emotion design, emotional branding