Showing papers in "Journal of New Music Research in 2003"
TL;DR: This article discusses the various approaches in representing musical genre, and proposes to classify these approaches in three main categories: manual, prescriptive and emergent approaches.
Abstract: Musical genre is probably the most popular music descriptor. In the context of large musical databases and Electronic Music Distribution, genre is therefore a crucial metadata for the description of music content. However, genre is intrinsically ill-defined and attempts at defining genre precisely have a strong tendency to end up in circular, ungrounded projections of fantasies. Is genre an intrinsic attribute of music titles, as, say, tempo? Or is genre a extrinsic description of the whole piece? In this article, we discuss the various approaches in representing musical genre, and propose to classify these approaches in three main categories: manual, prescriptive and emergent approaches. We discuss the pros and cons of each approach, and illustrate our study with results of the Cuidado IST project.
354 citations
TL;DR: This paper presents a review of a series of experiments which have contributed towards the understanding of the mapping layer in electronic instruments, and suggests that this can define the very essence of an instrument.
Abstract: This paper presents a review of a series of experiments which have contributed towards the understanding of the mapping layer in electronic instruments. It challenges the assumption that an electronic instrument consists solely of an interface and a sound generator. It emphasises the importance of the mapping between input parameters and sound parameters, and suggests that this can define the very essence of an instrument. The terms involved with mapping are defined, and existing literature reviewed and summarised. A model for understanding the design of such mapping strategies for electronic instruments is put forward, along with a roadmap of ongoing research focussing on the testing and evaluation of such mapping strategies.
338 citations
TL;DR: The Continuator is a system that bridges the gap between two classes of traditionally incompatible musical systems, based on a Markov model of musical styles augmented to account for musical issues such as management of rhythm, beat, harmony, and imprecision.
Abstract: We propose a system, the Continuator, that bridges the gap between two classes of traditionally incompatible musical systems: (1) interactive musical systems, limited in their ability to generate stylistically consistent material, and (2) music imitation systems, which are fundamentally not interactive. Our purpose is to allow musicians to extend their technical ability with stylistically consistent, automatically learnt material. This goal requires the ability for the system to build operational representations of musical styles in a real time context. Our approach is based on a Markov model of musical styles augmented to account for musical issues such as management of rhythm, beat, harmony, and imprecision. The resulting system is able to learn and generate music in any style, either in standalone mode, as continuations of musician’s input, or as interactive improvisation back up. Lastly, the very design of the system makes possible new modes of musical collaborative playing. We describe the architectu...
282 citations
TL;DR: An exhaustive review of research on automatic classification of sounds from musical instruments presents and discusses different techniques for similarity-based clustering of sounds and for classification into pre-defined instrumental categories.
Abstract: We present an exhaustive review of research on automatic classification of sounds from musical instruments. Two different but complementary approaches are examined, the perceptual approach and the taxonomic approach. The former is targeted to derive perceptual similarity functions in order to use them for timbre clustering and for searching and retrieving sounds by timbral similarity. The latter is targeted to derive indexes for labeling sounds after culture- or user-biased taxonomies. We review the relevant features that have been used in the two areas and then we present and discuss different techniques for similarity-based clustering of sounds and for classification into pre-defined instrumental categories.
204 citations
TL;DR: An audio fingerprinting system that uses the fingerprint of an unknown audio clip as a query on a fingerprint database, which contains the fingerprints of a large library of songs, the audio clip can be identified.
Abstract: Imagine the following situation. You’re in your car, listening to the radio and suddenly you hear a song that catches your attention. It’s the best new song you have heard for a long time, but you missed the announcement and don’t recognize the artist. Still, you would like to know more about this music. What should you do? You could call the radio station, but that’s too cumbersome. Wouldn’t it be nice if you could push a few buttons on your mobile phone and a few seconds later the phone would respond with the name of the artist and the title of the music you’re listening to? Perhaps even sending an email to your default email address with some supplemental information. In this paper we present an audio fingerprinting system, which makes the above scenario possible. By using the fingerprint of an unknown audio clip as a query on a fingerprint database, which contains the fingerprints of a large library of songs, the audio clip can be identified. At the core of the presented system are a highly robust fin...
191 citations
TL;DR: A system that facilitates the composition and perception of intricate, musically structured spatio-temporal patterns of vibration on the surface of the body is described, and some potential evolutionary branches of tactile composition are posited.
Abstract: What if the traditional relationship between touch and music was essentially turned upside down, making the tactile sensation the aesthetic end? This paper presents a novel coupling of haptics technology and music, introducing the notion of tactile composition or aesthetic composition for the sense of touch. A system that facilitates the composition and perception of intricate, musically structured spatio-temporal patterns of vibration on the surface of the body is described. Relevant work from disciplines including sensory substitution, electronic musical instrument design, simulation design, entertainment technology, and visual music is considered. The psychophysical parameter space for our sense of touch is summarized and the building blocks of a compositional language for touch are explored. A series of concerts held for the skin and ears is described, as well as some of the lessons learned along the way. In conclusion, some potential evolutionary branches of tactile composition are posited.
168 citations
TL;DR: In this paper, a multiple-pitch detection algorithm for polyphonic signals is used to calculate pitch histograms for audio signals, which are then evaluated in the context of automatic musical genre classification.
Abstract: In order to represent musical content, pitch and timing information is utilized in the majority of existing work in Symbolic Music Information Retrieval (MIR). Symbolic representations such as MIDI allow the easy calculation of such information and its manipulation. In contrast, most of the existing work in Audio MIR uses timbral and beat information, which can be calculated using automatic computer audition techniques. In this paper, Pitch Histograms are defined and proposed as a way to represent the pitch content of music signals both in symbolic and audio form. This representation is evaluated in the context of automatic musical genre classification. A multiple-pitch detection algorithm for polyphonic signals is used to calculate Pitch Histograms for audio signals. In order to evaluate the extent and significance of errors resulting from the automatic multiple-pitch detection, automatic musical genre classification results from symbolic and audio data are compared. The comparison indicates that Pitch H...
135 citations
TL;DR: The goal of this article is to review the different techniques proposed for melodic description and extraction, and some useful melodic transformations are reviewed.
Abstract: A huge amount of audio data is accessible to everyone by on-line or off-line information services and it is necessary to develop techniques to automatically describe and deal with this data in a meaningful way. In the particular context of music content processing it is important to take into account the melodic aspects of the sound. The goal of this article is to review the different techniques proposed for melodic description and extraction. Some ideas around the concept of melody are first presented. Then, an overview of the different ways of describing melody is done. As a third step, an analysis of the methods proposed for melody extraction is made, including pitch detection algorithms. Finally, techniques for melodic pattern induction and matching are also studied, and some useful melodic transformations are reviewed.
102 citations
TL;DR: Block Jam as mentioned in this paper is a Tangible User Interface (GUI) for controlling a dynamic polyrhythmic sequencer using 26 physical artifacts, called blocks, which are a new type of input device for manipulating an interactive music system.
Abstract: In this paper, we introduce Block Jam, a Tangible User Interface that controls a dynamic polyrhythmic sequencer using 26 physical artifacts These physical artifacts, that we call blocks, are a new type of input device for manipulating an interactive music system The blocks’ functional and topological statuses are tightly coupled to an ad hoc sequencer, interpreting the user’s arrangement of the blocks as meaningful musical phrases and structures We demonstrate that we have created both a tangible and visual language that enables both the novice and musically trained users by taking advantage of both their explorative and intuitive abilities The tangible nature of the blocks and the intuitive interface promotes face-to-face collaboration and social interaction within a single system Linking two Block Jam systems together to create a network further extends the principle of collaboration We discuss our project vision, design rational, related works, and the implementation of Block Jam prototypes
96 citations
TL;DR: The SOM-enhanced JukeBox (SOMeJB) is proposed, an approach to automatically create an organization of music archives following their perceived sound similarity using the Growing Hierarchical Self-Organizing Map, an unsupervised neural network.
Abstract: The availability of large music repositories calls for new ways of automatically organizing and accessing them. While artist-based listings or title indexes may help in locating a specific piece of music, a more intuitive, genre-based organization is required to allow users to browse an archive and explore its contents. So far, however, these organizations following musical styles have to be designed manually. With the SOM-enhanced JukeBox (SOMeJB) we propose an approach to automatically create an organization of music archives following their perceived sound similarity. More specifically, characteristics of frequency spectra are extracted and transformed according to psychoacoustic models. The resulting psychoacoustic Rhythm Patterns are further organized using the Growing Hierarchical Self-Organizing Map, an unsupervised neural network. On top of this advanced visualizations including Islands of Music (IoM) and Weather Charts offer an interface for interactive exploration of large music repositories.
93 citations
TL;DR: This paper is the first to use polyphonic audio queries to retrieve frompolyphonic symbolic collections, and will not only use an audio query to retrieve a known item symbolic piece, but will use it to retrieve an entire set of real-world composed variations on that piece, also in the symbolic format.
Abstract: This paper extends the familiar “query by humming” music retrieval framework into the polyphonic realm. As humming in multiple voices is quite difficult, the task is more accurately described as “query by audio example,” onto a collection of scores. To our knowledge, we are the first to use polyphonic audio queries to retrieve from polyphonic symbolic collections. Furthermore, as our results will show, we will not only use an audio query to retrieve a known item symbolic piece, but we will use it to retrieve an entire set of real-world composed variations on that piece, also in the symbolic format. The harmonic modeling approach which forms the basis of this work is a new and valuable technique which has both wide applicability and future potential.
TL;DR: It is argued that musical expression with multi-person instruments is a form of communication between the players, and it is illustrated that design for musical collaboration facilitates exploration of sound space with low entry-level skill.
Abstract: We explore the context and design of collaborative musical experiences for novices. We first argue that musical expression with multi-person instruments is a form of communication between the players. We illustrate that design for musical collaboration facilitates exploration of sound space with low entry-level skill. In contrast to the western post-Renaissance focus on musical expression through virtuosity, collaborative musical experiences enable the media of sound and music to enhance the communication opportunities and intimacy between players. The main factor common to most of the interfaces discussed herein is that musical control is highly restricted, which makes it possible for novices to easily learn and participate in the collective experience. This happens at the expense of providing an upward path to virtuosity with the interface. Balancing this tradeoff is a key concern for designers. We look closely at many contemporary collaborative interface designs, with each exploring a different way to ...
TL;DR: A first step towards automatic induction of multi-level models of expressive performance from real performances by skilled pianists is presented, and a hybrid learning system that learns to predict, via two different learning algorithms, both note-level and phrase-level expressive patterns, and combines these predictions into complex composite expression curves for new pieces.
Abstract: The article describes basic research in the area of machine learning and musical expression. A first step towards automatic induction of multi-level models of expressive performance (currently only tempo and dynamics) from real performances by skilled pianists is presented. The goal is to learn to apply sensible tempo and dynamics “shapes” at various levels of the hierarchical musical phrase structure. We propose a general method for decomposing given expression curves into elementary shapes at different levels, and for separating phrase-level expression patterns from local, note-level ones. We then present a hybrid learning system that learns to predict, via two different learning algorithms, both note-level and phrase-level expressive patterns, and combines these predictions into complex composite expression curves for new pieces. Experimental results indicate that the approach is generally viable; however, we also discuss a number of severe limitations that still need to be overcome in order to arrive ...
TL;DR: The use of computers in live performance has resulted in a situation in which cause-and-effect has effectively disappeared, for the first time since music began as mentioned in this paper, and the aim of this paper is to show how this affects contemporary performance and the relationship between the performer and the audience.
Abstract: The use of computers in live performance has resulted in a situation in which cause-and-effect has effectively disappeared, for the first time since music began. Once we started to use computers in live performance – to interpret gestures and generate sound as a result – the age-old relationship between gesture and result became so blurred as to be often imperceptible. In historical terms, this problem is extremely recent, involving only the last few decades of musical practice preceded by at least thirty thousand years of music-making by conventional (acoustic) means. The aim of this paper is to show how this affects contemporary performance and the relationship between the performer and the audience.
TL;DR: Potential applications of both watermarking and fingerprinting are described, showing which one is more suitable for each application.
Abstract: Although not a new issue, music piracy has acquired a new status in the digital era, as recordings can be easily copied and distributed. Watermarking has been proposed as a solution to this problem. It consists in embedding into the audio signal an inaudible mark containing copyright information. A different approach, called fingerprinting, consists in extracting a “fingerprint” from the audio signal. In association with a database, this fingerprint can be used to identify a recording, which is useful, for example, to monitor audio excerpts played by broadcasters and webcasters. There are far more applications to watermarking and fingerprinting. After a brief technical review, this article describes potential applications of both methodologies, showing which one is more suitable for each application.
TL;DR: This work aims to automate the task of music analysis, which involves transcription of audio into a representation with a similarity or distance metric, the search for similar segments, forming clusters ofsimilar segments, and explaining music in terms of these clusters.
Abstract: Human listeners are able to recognize structure in music through the perception of repetition and other relationships within a piece of music. This work aims to automate the task of music analysis. Music is “explained” in terms of embedded relationships, especially repetition of segments or phrases. The steps in this process are the transcription of audio into a representation with a similarity or distance metric, the search for similar segments, forming clusters of similar segments, and explaining music in terms of these clusters. Several pre-existing signal analysis methods have been used: monophonic pitch estimation, chroma (spectral) representation, and polyphonic transcription followed by harmonic analysis. Also, several algorithms that search for similar segments are described. Experience with these various approaches suggests that there are many ways to recover structure from music audio. Examples are offered using classical, jazz, and rock music.
TL;DR: A new model is suggested for computer understanding of sensory expressive intentions of a human performer and both theoretical and practical applications are described for human-computer interaction, perceptual information retrieval, creative arts and entertainment.
Abstract: Expressiveness is not an extravagance: instead, expressiveness plays a critical role in rational decision-making, in perception, in human interaction, in human emotions and in human intelligence. These facts, combined with the development of new informatics systems able to recognize and understand different kinds of signals, open new areas for research. A new model is suggested for computer understanding of sensory expressive intentions of a human performer and both theoretical and practical applications are described for human-computer interaction, perceptual information retrieval, creative arts and entertainment. Recent studies demonstrated that by opportunely modifying systematic deviations introduced by the musician it is possible to convey different sensitive contents, such as expressive intentions and/or emotions. We present an space, that can be used as a user interface. It represents, at an abstract level, the expressive content and the interaction between the performer and an expressive synthesizer.
TL;DR: This article describes the transformation process itself, including the main model schemes that are commonly used, which lead to the establishment of the formal basis for a definition of content-based transformations.
Abstract: Content processing is a vast and growing field that integrates different approaches borrowed from the signal processing, information retrieval and machine learning disciplines. In this article we deal with a particular type of content processing: the so-called content-based transformations. We will not focus on any particular application but rather try to give an overview of different techniques and conceptual implications. We first describe the transformation process itself, including the main model schemes that are commonly used, which lead to the establishment of the formal basis for a definition of content-based transformations. Then we take a quick look at a general spectral based analysis/synthesis approach to process audio signals and how to extract features that can be used in the content-based transformation context. Using this analysis/synthesis approach we give some examples on how content-based transformations can be applied to modify the basic perceptual axis of a sound and how we can even co...
TL;DR: In order for MIR to succeed, researchers need to work with real user communities and develop research resources such as reference music collections, so that the wide variety of techniques being developed in MIR can be meaningfully compared with one another.
Abstract: Music Information Retrieval (MIR) is an interdisciplinary research area that has grown out of the need to manage burgeoning collections of music in digital form. Its diverse disciplinary communities, exemplified by the recently established ISMIR conference series, have yet to articulate a common research agenda or agree on methodological principles and metrics of success. In order for MIR to succeed, researchers need to work with real user communities and develop research resources such as reference music collections, so that the wide variety of techniques being developed in MIR can be meaningfully compared with one another. Out of these efforts, a common MIR practice can emerge.
TL;DR: The evolution of the technology of the Tabla from its origins until the present day is described; the traditional playing style of theTabla, on which the controller is modeled; the creation of a real-time Tabla controller, using force-sensors; the physical modeling of the sound of the tabla using banded waveguide synthesis.
Abstract: This paper describes the design of an electronic Tabla controller (ETabla). Tabla are a pair of hand drums traditionally used to accompany North Indian vocal and instrumental music. The ETabla controls both sound and graphics simultaneously. It allows for a variety of traditional Tabla strokes and new performance techniques. Graphical feedback allows for artistic display and has potential pedagogical applications. This paper describes the evolution of the technology of the Tabla from its origins until the present day; the traditional playing style of the Tabla, on which the controller is modeled; the creation of a real-time Tabla controller, using force-sensors; the physical modeling of the sound of the Tabla using banded waveguide synthesis; the creation of a real-time graphics feedback system that reacts to the Tabla controller; experiments on measuring the response time of the ETabla sensors; and the description of the ETabla used in a live performance.
TL;DR: It is concluded that phrasing was a prominent principle in this performance and that rule combinations have to change between sections in order to match this pianist’s deviations.
Abstract: The Director Musices generative grammar of music performance is a system of context dependent rules that automatically introduces expressive deviation in performances of input score files. A number ...
TL;DR: A series of controllers that exploit the musical possibilities of this architecture – the somewhat constrained Musical Trinkets, where objects were tied to simple notes and musical effects, and its successor, the Musical Navigatrics, which enabled dynamic overdubbing and control of complex musical sequences and sonic textures.
Abstract: This paper describes the development of a musical interface based on electromagnetic tagging technology, where an ensemble of passively tagged objects is identified and tracked in real time when placed in the vicinity of a reader. As the system is able to identify and update the state of many (30 or more) tags simultaneously, they can be used together in any combination – e.g., several can sit on a surface at fixed distances from the reader while others can be handheld or worn by a single user or multiple performers. This interface is able to detect both free gesture (position and orientation of the objects) as well as local or tactile variables (e.g., pressure). We describe a series of controllers that exploit the musical possibilities of this architecture – the somewhat constrained Musical Trinkets, where objects were tied to simple notes and musical effects, and its successor, the Musical Navigatrics, which enabled dynamic overdubbing and control of complex musical sequences and sonic textures. We close with a description of a very simple and inexpensive actively-tagged tracking system capable of much wider range.
TL;DR: An automatic music playlist generator called PATS (Personalized Automatic Track Selection) creates playlists that aim at suiting a particular listening situation and showed that PATS playlists contained increasingly more preferred music, covered more preferredMusic in the collection, and were rated higher than randomly assembled playlists.
Abstract: An automatic music playlist generator called PATS (Personalized Automatic Track Selection) creates playlists that aim at suiting a particular listening situation. It uses dynamic clustering in which songs are grouped based on a weighted attribute-value similarity measure. An inductive learning algorithm is used to reveal the weights for attribute-values using user preference feedback. In a controlled user experiment, the quality of PATS-generated and randomly assembled playlists for jazz music was assessed in two listening situations. The two listening situations were “listening to soft music” and “listening to lively music.” Playlist quality was measured by precision (songs that suit the listening situation), coverage (songs that suit the listening situation but that were not already contained in previous playlists) and a rating score. Results showed that PATS playlists contained increasingly more preferred music (increasingly higher precision), covered more preferred music in the collection (higher cove...
TL;DR: An algorithm that checks for melodic similarity and a music summarization system called Papipuun, which can produce a music summary of good quality with a symbolic approach, reflecting the atmosphere of an entire piece through interaction with the user.
Abstract: This paper presents an algorithm that checks for melodic similarity and a music summarization system called “Papipuun.” First, we developed a data structure for representing polyphony based on a time-span reduction in the generative theory of tonal music (GTTM) and the deductive object-oriented database (DOOD). A least upper bound operation is introduced to check the similarity of polyphonies represented in our method. Next, Papipuun performs quick listening in a manner similar to stylus skipping on a scratched record, but the skipping occurs correctly at punctuations of musical phrases, not arbitrarily. Papipuun can produce a music summary of good quality with a symbolic approach, reflecting the atmosphere of an entire piece through interaction with the user. In a pre-processing phase of Papipuun, a user analyzes an input piece by time-span reduction, using a dedicated tool called TS-Editor. For the real-time phase, the user interacts with the main system, Summarizer, to perform music summarization. The ...
TL;DR: It is argued that investigations of rhythm in music content processing applications should be listener-oriented, signal-oriented and application-oriented; and the bottom-up and top-down oriented approaches to computational modeling are commented.
Abstract: This paper is concerned with the handling of rhythm in music content processing applications. Keeping this framework in mind, we briefly report on terminology issues and the interdisciplinary nature of rhythm investigations, we then review approaches to computational modeling of rhythm and rhythm representation schemes. We comment the bottom-up and top-down oriented approaches to computational modeling and the parallel that some authors make with physiological and cognitive views on rhythm perception. We argue that investigations should be listener-oriented, signal-oriented and application-oriented.
TL;DR: Electronic music controllers evolve so rapidly that it’s rare for a musician to work long enough with one to develop virtuosic technique, keeping the field in continual revolution and allowing few instruments to be mastered by a significant community of players.
Abstract: (2003). Current Trends in Electronic Music Interfaces. Guest Editors’ Introduction. Journal of New Music Research: Vol. 32, No. 4, pp. 345-349.
TL;DR: The hypotheses in the present study were that certain pitches relative to tonality are important for specific emotional expressions, and that their importance is further increased by being emphasized either by immanent or performed accents.
Abstract: Psychology of music has shown renewed interest in how music expresses emotion to listeners. However, there is an obvious lack of research on how interactions between musical factors such as harmony, rhythm, melodic contour, loudness, and articulation may affect perceived emotion. From previous literature on music analysis and music cognition there is evidence that tonality may be activated and affected by rhythm and melody. These ideas generated hypotheses regarding melodic organization and performance, for instance, (a) certain notes in a melodic structure have expressive potentials due to their place in the key/chord, (b) these notes could be activated by accents in the melodic structure and/or in live music performance. In Study I, a simple tune was systematically manipulated with regard to harmonic progression, rhythm and melodic contour. Listener ratings of the resulting versions showed that perceived structure (instability, complexity, tension) and emotion (sadness, anger, expressivity) could be partly interpreted as resulting from accent structures and stress on certain notes. In Study II, musicians were asked to perform some of the above-mentioned versions so as to express happiness, sadness, tenderness and anger. The performers used loudness and articulation to compensate for lack of adequate inherent expression in melodies. They also highlighted certain notes of relevance for the emotional meaning by means of stress in articulation, loudness and timing. In Study III, simple three-note sequences were manipulated with regard to melodic, metric and rhythmic accents as well as (computer-) performed accents (loudness, articulation and timing) on certain target notes. Listening tests showed that accent on a tense note enhanced perceived anger. A note essential for the identity of major mode affected perception of happiness, whereas a note essential for minor mode affected perception of sadness. The results in this thesis have implications for a dynamic view of melodic organization and performance.
TL;DR: This work presents a methodology for the estimation of the rule parameters to reproduce a given human performance as closely as possible and allows an objective comparison of parameter sets already studied in literature.
Abstract: In studies of music performance, rule systems have been used to model the expressive deviations introduced by musicians. In this work we present a methodology for the estimation of the rule parameters to reproduce a given human performance as closely as possible. To achieve best fit, a least square algorithm was used. The estimation can be carried out on different time scales to improve the fit when the performer used different expressive strategies during the piece. The method has been tested on different pieces, recorded both in a controlled experiment, and also in ecological settings. Results confirm this methodology, and allow an objective comparison of parameter sets already studied in literature. The model can also be used to compare different rule systems, both from a numerical point of view, and also by listening the synthesized performances obtained using the estimated values.
TL;DR: An attempt is presented to classify concert music performances played by different performers (and hence characterized by different expressive styles), obtained from statistical analysis of a set of simple audio cues extracted in real time by aSet of tools implemented in the EyesWeb open platform.
Abstract: In this paper an attempt is presented to classify concert music performances played by different performers (and hence characterized by different expressive styles). The classification is obtained from statistical analysis of a set of simple audio cues, extracted in real time by a set of tools implemented in the EyesWeb open platform. The cue extraction process is carried out by looking at a “note” and a “phrase” profile (obtained by squaring and low pass filtering the audio signal). These are exploited to obtain, for each note, parameters regarding tempo, articulation and dynamics. Statistical analysis is then performed on the extracted data in order to establish whether more or less remarkable differences among the original performances can be traced. Once this is confirmed, a Hidden Markov Model is proposed, developed in MatLab and able to recognize the players’ styles on the basis of audio cues.
TL;DR: In this article, an uninterrupted recording of Erik Satie's "Vexations" performed by one pianist over almost 28 hours is used as a performance of extreme length to explore new approaches in performance data analysis.
Abstract: This study extends the perspective of music performance research with an examination of a long-term performance. In a single case study, an uninterrupted recording of Erik Satie’s “Vexations” performed by one pianist over almost 28 hours is used as a performance of extreme length to explore new approaches in performance data analysis. The MIDI and acoustical data are analysed with linear and non-linear methods to describe changes in tempo and loudness. Additionally, the performer’s changing states of consciousness (alertness, trance, drowsiness) were observed to exert a strong influence on tempo and loudness stability. Tempo and loudness remain stable over the first 14 hours of alertness. A state of trance begins after 15 hours and shows a destabilisation of tempo followed by uncontrolled deviations in loudness. Time series analysis of loudness changes revealed periodicities of about 10 minute lengths. Non-linear analyses of tempo and loudness changes showed a complex generator pattern underlying the apparently random fluctuations throughout the performance. This pattern appears most clearly when unfolded in an 18-dimensional embedding space. Measures of fractality and chaotic behavior proved to be dependent on the states of consciousness. Results are discussed in regard to influences of psycho-physiological changes (vigilance) on sensorimotor performance and to the overall stability of an oscillating psycho-motoric system. “The artist does not have the right to take up the audience’s time unnecessarily.”