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Music Representation and Transformation in Software = Structure and Algorithms in Python /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Music Representation and Transformation in Software/ by Donald P. Pazel.
其他題名:	Structure and Algorithms in Python /
作者:	Pazel, Donald P.
面頁冊數:	XX, 333 p. 204 illus., 27 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Software engineering. -
電子資源:	https://doi.org/10.1007/978-3-030-97472-5
ISBN:	9783030974725

Music Representation and Transformation in Software = Structure and Algorithms in Python /
Pazel, Donald P.

Music Representation and Transformation in SoftwareStructure and Algorithms in Python /[electronic resource] :by Donald P. Pazel. - 1st ed. 2022. - XX, 333 p. 204 illus., 27 illus. in color.online resource.

Part 1: Representation -- 1. Software Modeling and Object-Oriented Design -- 2. The Chromatic Scale and the Diatonic Foundation -- 3. Intervals -- 4. Modality, Tonality, and Scales -- 5. Time in Music -- 6. The Note and Note Aggregates -- 7. Chords -- 8. Instruments -- 9. Score Representation -- 10. Rendering Score to Midi -- 11. Variable Dynamics and Tempo -- 12. Further Representations -- Part 2: Music Transformations -- 13. An Introduction to Music Transformations -- 14. A Constraint Engine for Pitch Assignment -- 15. Shift: A Transform fKey Change -- 16. Reflection: A Transform for Melodic Inversion -- 17. Reshape: A Transform for Melodic Shaping -- 18. Harmonic Transcription: Preserving Melody Over Harmonic Change -- 19. Retrograde: Reversing a Melody -- 20. Melodic Search and Pattern Substitution -- 21 Dilation: Musical Expansion and Contraction -- 22. The Step Shift Transform and Sequences -- 23. Final Thoughts.

This book takes the reader on a journey through music concepts in an organized approach that develops music essentials from the concepts of tone, pitch, and time, through notes, intervals, chords, and scores while at the same time interpreting these elements as software artifacts. Close attention is paid to the organization of and relationships amongst these concepts and their representation as Python classes and objects, to learn about music from a software design viewpoint. The first part of the book focuses on software representation of the main elements found in music theory. Its objective is to provide direction to students on how to build a music software model from basic concepts and grow towards more complex concepts. Chapter by chapter, music concepts are introduced, and each is broken apart into related data properties and methods with the goal that by the end of this section, the reader will have developed a relatively complete library of music elements in software. The second part takes on the task of applying that foundation to the subject of “music transformations”. The focus is on localized transformations, that is, transformations isolated to a few measures. After a general introduction, the discussion includes topics of pitch assignment, key change, melodic inversion, melodic shaping, harmonic transcription, retrograde, melodic search and dilation. This textbook is designed as a principal or supplemental source for computer science, software engineering, and programming courses. It can also be used as a main textbook for advanced computer music courses or electronic music courses. Computer music software professionals interested in learning how to model the complexities of music theory artifacts, or music students who want to learn advanced programming techniques in their domain will also find the book helpful.

ISBN: 9783030974725

Standard No.: 10.1007/978-3-030-97472-5doiSubjects--Topical Terms:

562952
Software engineering.

LC Class. No.: QA76.758

Dewey Class. No.: 005.1

Music Representation and Transformation in Software = Structure and Algorithms in Python /
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520 $a This book takes the reader on a journey through music concepts in an organized approach that develops music essentials from the concepts of tone, pitch, and time, through notes, intervals, chords, and scores while at the same time interpreting these elements as software artifacts. Close attention is paid to the organization of and relationships amongst these concepts and their representation as Python classes and objects, to learn about music from a software design viewpoint. The first part of the book focuses on software representation of the main elements found in music theory. Its objective is to provide direction to students on how to build a music software model from basic concepts and grow towards more complex concepts. Chapter by chapter, music concepts are introduced, and each is broken apart into related data properties and methods with the goal that by the end of this section, the reader will have developed a relatively complete library of music elements in software. The second part takes on the task of applying that foundation to the subject of “music transformations”. The focus is on localized transformations, that is, transformations isolated to a few measures. After a general introduction, the discussion includes topics of pitch assignment, key change, melodic inversion, melodic shaping, harmonic transcription, retrograde, melodic search and dilation. This textbook is designed as a principal or supplemental source for computer science, software engineering, and programming courses. It can also be used as a main textbook for advanced computer music courses or electronic music courses. Computer music software professionals interested in learning how to model the complexities of music theory artifacts, or music students who want to learn advanced programming techniques in their domain will also find the book helpful.
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