Music and Artificial Intelligence: Second International Conference, ICMAI 2002, Edinburgh, Scotland, UK, September 12-14, 2002, Proceedings: Lecture Notes in Computer Science, cartea 2445
Editat de Christina Anagnostopoulou, Miguel Ferrand, Alan Smaillen Limba Engleză Paperback – 28 aug 2002
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Specificații
ISBN-13: 9783540441458
ISBN-10: 354044145X
Pagini: 220
Ilustrații: VIII, 212 p.
Dimensiuni: 155 x 235 x 12 mm
Greutate: 0.52 kg
Ediția:2002
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 354044145X
Pagini: 220
Ilustrații: VIII, 212 p.
Dimensiuni: 155 x 235 x 12 mm
Greutate: 0.52 kg
Ediția:2002
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
Invited Talks.- Structure and Interpretation of Music Concepts: Music from a Computational Perspective.- Expressive Gesture.- Regular Contributions.- A General Parsing Model for Music and Language.- The Spiral Array: An Algorithm for Determining Key Boundaries.- Representation and Discovery of Vertical Patterns in Music.- Discovering Musical Structure in Audio Recordings.- Real Time Tracking and Visualisation of Musical Expression.- Automatic Classification of Drum Sounds: A Comparison of Feature Selection Methods and Classification Techniques.- Some Formal Problems with Schenkerian Representations of Tonal Structure.- Respiration Reflecting Musical Expression: Analysis of Respiration during Musical Performance by Inductive Logic Programming.- Mimetic Development of Intonation.- Interacting with a Musical Learning System: The Continuator.- Recognition of Isolated Musical Patterns Using Hidden Markov Models.- A Model for the Perception of Tonal Melodies.- Control Language for Harmonisation Process.- Evaluating Melodic Segmentation.- Combining Grammar-Based and Memory-Based Models of Perception of Time Signature and Phase.- A Bayesian Approach to Key-Finding.
Caracteristici
Includes supplementary material: sn.pub/extras