The Impact of the Digital Instrument and the Score on Controlled Improvisation When using Acoustic Instruments in an Electroacoustic Context

This paper considers various elements that influence the decisions taken when designing performance environments for compositions featuring acoustic instruments with electronics. The implications of choosing different models for the control of the electronics are discussed. Models lying along a continuum between fully automated systems at one end and passive environments controlled by a human performer at the other are considered. The ways in which choices made when mapping control parameters to the sound engine affect the affordances available to the human performer are explored, and the advantages of using a score to define parameters for improvisation are discussed. Following from this, different models for notating the electronic part in mixed compositions are presented and the implication of using the computer as the principal agent for controlling the electronic part are considered. This leads into a discussion as to what constitutes a score for the electronic part. Different paradigms are presented and their implications considered. The paper then discusses the ease of encoding and decoding musical information at different representational levels into and out of a computer. This has implications for machine learning and score following systems. The paper concludes by presenting an example of a digital performance environment from the author’s own work, together with a score for controlled improvisation using the interface

The Emotional Characteristics of Bowed String Instruments with Different Pitch and Dynamics

Previous research has shown that different musical instrument sounds have strong emotional characteristics. This paper investigates how emotional characteristics vary with pitch and dynamics within the bowed string instrument family. We conducted listening tests to compare the effects of pitch and dynamics on the violin, viola, cello, and double bass. Listeners compared the sounds pairwise over 10 emotional categories. Results showed that the emotional characteristics Happy, Heroic, Romantic, Comic, and Calm generally increased with pitch but decreased at the highest pitches. Angry and Sad generally decreased with pitch. Scary was strong in the extreme low and high registers, while Shy and Mysterious were unaffected by pitch. For dynamics, the results showed that Heroic, Comic, and Angry were stronger for loud notes, while Romantic, Calm, Shy, Sad, and the high register for Happy were stronger for soft notes. Scary and Mysterious were unaffected by dynamics. The results also showed significant differences between different bowed string instruments on notes of the same pitch and dynamic level. These results help quantify our understanding of the relative emotional characteristics of the strings. They provide audio engineers and musicians with suggestions for emphasizing emotional characteristics of the bowed strings in sound recordings and performances

Notation Sequence Generation and Sound Synthesis in Interactive Spectral Music

Notation sequence generation and sound synthesis in interactive spectral music This thesis consists of a preliminary analysis of existing spectral music paradigms and proposes a methodology to address issues that arise in real-time spectral music composition and performance scenarios. This exploration involves an overview of meaning in spectral music with a particular focus on the ‘sonic object’ as a vehicle for expression. A framework for the production of ‘interactive spectral music’ was created. This framework takes form as a group of software based compositional tools called SpectraScore developed for the Max for Live platform. Primarily, these tools allow the user to analyse incoming audio and directly apply the collected data towards the generation of synthesised sound and notation sequences. Also presented is an extension of these tools, a novel system of correlation between emotional descriptors and spectrally derived harmonic morphemes. The final component is a portfolio of works created as examples of the techniques explored in scored and recorded form. As a companion to these works, an analysis component outlines the programmatic aspects of each piece and illustrates how they are executed within the music. Each scored piece corresponds with a recording of a live performance or performances of the work included in the attached DVD, which comprises individual realisations of the interactive works. Keywords: Spectralism, Music and Emotion, Electronic Music, Spectral Music, Algorithmic Music, Real-time Notatio

Notation Sequence Generation and Sound Synthesis in Interactive Spectral Music

Notation sequence generation and sound synthesis in interactive spectral music This thesis consists of a preliminary analysis of existing spectral music paradigms and proposes a methodology to address issues that arise in real-time spectral music composition and performance scenarios. This exploration involves an overview of meaning in spectral music with a particular focus on the ‘sonic object’ as a vehicle for expression. A framework for the production of ‘interactive spectral music’ was created. This framework takes form as a group of software based compositional tools called SpectraScore developed for the Max for Live platform. Primarily, these tools allow the user to analyse incoming audio and directly apply the collected data towards the generation of synthesised sound and notation sequences. Also presented is an extension of these tools, a novel system of correlation between emotional descriptors and spectrally derived harmonic morphemes. The final component is a portfolio of works created as examples of the techniques explored in scored and recorded form. As a companion to these works, an analysis component outlines the programmatic aspects of each piece and illustrates how they are executed within the music. Each scored piece corresponds with a recording of a live performance or performances of the work included in the attached DVD, which comprises individual realisations of the interactive works. Keywords: Spectralism, Music and Emotion, Electronic Music, Spectral Music, Algorithmic Music, Real-time Notatio

Timbral Use of the Handbell Ensemble: Background, Analysis, and Strategies

With new technology, handbells can have a clear tone on which almost any melody can be played clearly. Despite a growing body of composers and repertoire for the handbell ensemble, the relative number of top-level contemporary compositions and truly professional ensembles is small. A recent necessary standardization of notation resulted in ubiquitous arrangements, misrepresenting the handbell ensemble’s vast sonic possibilities and often diminishing its connection to its worldwide historical roots. However, the handbell is an instrument of “timbre;” it can produce many more sounds than are being used. This dissertation aims to convince musical communities that this composite instrument is capable of more than enough sonic expression to carry or support any contemporary composition. To do this, the study explores relevant history and early repertoire, presents new sounds in newer repertoire, and catalogues and analyzes the handbell’s sounds (and the sounds of the related instrument, the handchime) into a Handbell and Handchime Timbre Dictionary. The study concludes by proposing eight strategies for the new handbell ensemble, including that composers should learn to use the handbell ensemble timbrally and combine it with other instrumentations. By doing so, the genre of the handbell ensemble can grow and mature into its promising potential

The Effects of Reverberation on the Emotional Characteristics of Musical Instruments

Though previous research has shown the effects of reverberation on clarity, spaciousness, and other perceptual aspects of music, it is still largely unknown to what extent reverberation influences the emotional characteristics of musical instrument sounds. This paper investigates the effect of simple parametric reverberation on music emotion, in particular, the effect of reverberation length and amount. We conducted a listening test to compare the effect of reverberation on the emotional characteristics of eight instrument sounds representing the wind and bowed string families. We compared these sounds over eight emotional categories. We found that reverberation length and amount had a strongly significant effect on the emotional characteristics Romantic and Mysterious and a medium effect on Sad, Scary, and Heroic for the samples we tested. Interestingly, for Comic, reverberation length and amount had the opposite effect; that is, anechoic tones were judged most Comic. Reverb had a mild effect on Happy and relatively little effect on Shy. These results give audio engineers and musicians an interesting perspective on simple parametric artificial reverberation

Extending physical instruments using sampled acoustics

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2007.Includes bibliographical references (p. 133-138).This thesis presents a system architecture for creating hybrid digital-acoustic percussion instruments by combining extensions of existing signal processing techniques with specially-designed semi-acoustic physical controllers. This work aims to provide greater realism to digital percussion, gaining much of the richness and understandability of acoustic instruments while preserving the flexibility of digital systems. For this thesis, I have collaborated with percussionists to develop a range of instruments, to refine and extend the algorithmic and physical designs, and to determine successful models of interaction. Conventional percussion controllers measure and discretize the intensity of strikes into discrete trigger messages, but they also ignore the timbre of the hits and fail to track more ambiguous input. In this work, the continuous acoustic output of a struck physical object is processed to add the resonance of a sampled instrument. This is achieved by employing existing low-latency convolution algorithms which have been extended to give the player control over features such as damping, spectral flattening, nonlinear effects, and pitch.(cont.) One of the advantages of this approach is that light taps, scrapes, rubs, or stirring with brushes all take on a hybrid timbre of the real and sampled sound that is surprisingly realistic and controllable. Since part of its behavior is inherently acoustic, a player's intuition about interacting with physical objects can be applied to controlling it. The ability to transform the apparent acoustic properties of objects also suggests applications to HCI and product design contexts.by Roberto Mario Aimi.Ph.D

Understanding Music: Past and Present

Understanding Music: Past and Present is an open Music Appreciation textbook co-authored by music faculty across Georgia. The text covers the fundamentals of music and the physics of sound, an exploration of music from the Middle Ages to the present day, and a final chapter on popular music in the United States. Accessible files with optical character recognition (OCR) and auto-tagging provided by the Center for Inclusive Design and Innovation.https://oer.galileo.usg.edu/arts-textbooks/1000/thumbnail.jp

An Investigation into How Reverberation Effects the Space of Instrument Emotional Characteristics

Previous research has shown that musical instruments have distinctive emotional characteristics and that these characteristics can be significantly changed with reverberation. This paper considers whether these changes in character are relatively uniform or instrument-dependent. We compared eight sustained instrument tones with different amounts and lengths of simple parametric reverberation over eight emotional characteristics. The results show a remarkable consistency in listener rankings of the instruments for each of the different types of reverberation, with strong correlations ranging from 90 to 95%. These results indicate that the underlying instrument space does not change much with reverberation in terms of emotional characteristics, and that each instrument has a particular footprint of emotional characteristics. Among the tones we tested, the instruments cluster into two fairly distinctive groups: those where the positive energetic emotional characteristics are strong (e.g., oboe, trumpet, violin) and those where the low-arousal characteristics are strong (e.g., bassoon, clarinet, flute, horn). The saxophone is an outlier and is somewhat strong for most emotional characteristics. In terms of applications, the relatively consistent rankings of emotional characteristics between the instruments certainly helps each instrument retain its identity in different reverberation environments and suggests possible future work in instrument identification