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Abstract. Today, many private households as well as broadcasting or film companies own large collections of digital music plays. These are time series that differ from, e.g., weather reports or stocks market data. The task is normally that of classification, not prediction of the next value or recognizing a shape or motif. New methods for extracting features that allow to classify audio data have been developed. However, the development of appropriate feature extraction methods is a tedious effort, particularly because every new classification task requires tailoring the feature set anew. This paper presents a unifying framework for feature extraction from value series. Operators of this framework can be combined to feature extraction methods automatically, using a genetic programming approach. The construction of features is guided by the performance of the learning classifier which uses the features. Our approach to automatic feature extraction requires a balance between the completeness of the methods on one side and the tractability of searching for appropriate methods on the other side. In this paper, some theoretical considerations illustrate the trade-off. After the feature extraction, a second process learns a classifier from the transformed data. The practical use of the methods is shown by two types of experiments: classification of genres and classification according to user preferences. 1.

MAD (Movie Authoring and Design) is a novel design and authoring system that facilitates the process of creating dynamic visual presentations such as motion pictures and lecture-demonstrations. MAD supports the process by enhancing the author's ability to structure and modify a presentation and to visualize the ultimate result. It does this by allowing both top-down design and bottom-up creation with a hierarchical multimedia document representation; by supporting the flexible inclusion and combination of words, images, sounds, and video sequences; and by providing real-time playback of the best approximation to the ultimate presentation that can be produced at any stage of the design process.

Canon is both a notation for musical scores and a programming language. Canon offers a combination of declarative style and a powerful abstraction capability which allows a very high-level notation for sequences of musical events and structures. Transformations are operators that can adjust common parameters such as loudness or duration. Transformations can be nested and time-varying, and their use avoids the problem of having large numbers of explicit parameters. Behavioral abstraction, the concept of making behavior an arbitrary function of the environment, is supported by Canon and extends the usefulness of transformations. A non-real-time implementation of Canon is based on Lisp and produces scores that control MIDI synthesizers. Introduction Canon is a computer language designed to help composers create note-level control information for hardware synthesizers or synthesis software. Canon was motivated by my need for a simple yet powerful language for teaching second-semester stud...

The Piano Tutor provides computer-based instruction to beginning piano students. Intended as a supplement to traditional instruction, the Piano Tutor helps students by correcting mistakes before they become ingrained through practice and by teaching new material as soon as the student is ready. The Piano Tutor combines an expert system with state-of-the-art music recognition software and multimedia output devices to provide a stimulating learning environment that tailors instruction to the student’s needs. 1.

This thesis describes an approach to representing musical rhythm in computational terms. The purpose of such an approach is to provide better models of musical time for machine accompaniment of human musicians and in that attempt, to better understand the processes behind human perception and performance. The intersections between musicology and artificial intelligence (AI) are reviewed, describing the rewards from the interdisciplinary study of music with AI techniques, and the converse benefits to AI research. The arguments for formalisation of musicological theories using AI and cognitive science concepts are presented. These bear upon the approach of research, considering ethnographic and process models of music versus traditionally descriptive methods of music study. This enquiry investigates the degree to which the human task of music can be studied and modelled computationally. It simultaneously performs the AI task of problem domain identification and constraint. The psycholo...

. A set of techniques have been developed and refined to support the demanding software requirements of combined interactive computer music and computer animation. The techniques include a new programming environment that supports an integration of procedural and declarative score-like descriptions of interactive real-time behavior. Also discussed are issues of asynchronous input, concurrency, memory management, scheduling, and testing. Two examples are described. Keywords: music, interactive, composition, MIDI, multimedia, software 1. Introduction My work for the past few years has focused on the use of real-time computer systems to carry on compositional processes during a performance. The rationale behind this work is that composing during a performance allows a work of music to benefit from the ideas of a composer as well as those of an improviser. Of course, this could be said about many approaches ranging from aleatoric music to jazz. Almost all music contains elements of compo...

Statistical modeling and analysis have been applied to different music related fields. One of them is sound synthesis and analysis. Sound can be represented as a real-valued function of time. This function can be sampled at a small enough rate so that the resulting discrete version is almost as good as the continuous one. This permits one to study musical sounds as a discrete time series, an entity for whichmany statistical techniques are available. Physical modeling suggests that manymusical instruments' sounds are characterized bya harmonic and an additive noise signal. The noise is not something to get rid of rather it's an important part of the signal. In this research the interest is in separating these two elements of the sound. To do so a local harmonic model that tracks ch...

Many recent computer applications seek to support or even participate in structured collaborations with humans. Examples range from computer-supported collaborative work to interactive music systems. This thesis presents a general model for structured collaboration based on conversational turn-taking. According to the model, collaboration participants share both a representation of the collaboration's structure and the algorithms governing navigation through that structure. ImprovisationBuilder, an object-oriented framework written in Smalltalk-80, supports this model for musical improvisation. The framework demonstrates how computers can participate in musical improvisation, and how the study of conversation can improve that participation. Two musical improvisational domains are described. The first is a free-form three part canon defined by Sal Martirano's Sound and Logic system. The second is the tradition of small jazz ensemble performance made popular in the 1940's and 50's. Impro...

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