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Presentation
Presentation
This course is focused on Digital Signal Processing (DSP), with a strong emphasis on sound and music applications. The Unit aims to provide a solid foundation on the physical and mathematical representations of sound, and sound processing systems. The program covers important theories and applications related to sampling, filters, sound synthesis algorithms, sound transformations, temporal and spectral analysis, and analysis/resynthesis methods. As a part of the masters curriculum, the Unit is justified not only by addressing the theoretical, mathematical and scientific basis of sound, but also by developing the students practical skills through sound programming languages.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Master Degree | Semestral | 6
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT2722-16190
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
The syllabus emerges from philosophical and aesthetic issues, develops on the basis of mathematics and physics, and is explored in practice through sound programming languages. The starting point is the sound phenomenon, both from the point of view of acoustic properties and listening. The multiple dimensions of sound (timbre, pitch, loudness, space, duration, etc.) as well as the various forms of symbolic representation are discussed. The temporal and spectral domains underlie the reflection on the analysis / resynthesis methods, and on the synthesis and signal processing techniques. The history and aesthetics of electronic music supports the understanding of the development of technological tools. Key points of the course:
- sinusoidal waves and time invariant linear systems
- impulse response, frequency response, convolution and filters
- Fourier transform and transfer function
- sinusoidal, harmonic and sinusoidal + residual model
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Objectives
Objectives
The knowledge, skills and competences to be developed by students can be linked as follows:
1. Assimilate the multiplicity of scientific approaches to the sound phenomenon.
2. Master the mathematical tools needed to study Digital Signal Processing (DSP)
3. Know the different methods and techniques of sound synthesis, including additive, subtractive, fm, granular, physical modeling synthesis, among others.
4. Understand the diversity of sound transformations, including filters, ring modulation, convolution, among others.
5. Understand the different representations of sound and the different methods of analysis / resynthesis, as well as the possible manipulations in the temporal and spectral domains.
6. Frame technological procedures in the context and practice of music informatics.
7. Materialize the tools and concepts in applications and projects of digital audio and computer and electroacoustic music, both in an individual context and in network art.
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Teaching methodologies and assessment
Teaching methodologies and assessment
The teaching methodology consists of theoretical classes (using audiovisual and multimedia materials) and practical classes, centered on the synthesis and processing of audio signals.
Combining theoretical problems with mastery of advanced sound programming languages ¿¿(e.g. Supercollider, Faust), encourages innovative and up to date approaches.
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References
References
Boulanger, R. (ed.) (2010) The CSound Book: perspectives in software synthesis, sound design, signal processing, and programming. MIT Press
Mitra, S. (1998) Digital Signal Processing: a computer-based approach. McGraw Hill
Miranda, E.R. (2002) Computer Sound Design: Synthesis techniques and programming. Focal Press
Park, T. H. (2010) Introduction to Digital Signal Processing: computer musically speaking. World Scientific
Roads, C; Pope, S.T., et al. (ed) (1997) Musical Signal Processing. Swets & Zeitlinger
Russ, M. (2009) Sound Synthesis and Sampling. Focal Press
Tempelaars, S. (1996) Signal Processing, Speech and Music. Routledge
Wilson, S. (ed.) (2011) The Supercollider Book. MIT Press
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Office Hours
Office Hours
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Mobility
Mobility
No
