Computer based sound production

Subject description

Introduction and overview of the field.

• Basics of sound and computer based production:

o physics (amplitude, frequency, phase, speed, interference, resonan-ce, power, other wave phenomena);

o mathematics (Fourier theory, sampling theory, convolution, corre-lation, Hilbert transform, Gabor’s acoustic quant and transfrom, etc.);

o physiology and psychoacoustics (aural perception, frequency range, indirect perception by various anatomical structures, the role of harmonics, localization, masking, critical bands, environment-tal effects, latest neuroscience research results in this domain).

• Electronic and network principles of sound processing: analog and digital signal, (quantization) noise, medium / device bandwidth, amplification and attenuation, analog to digital, and digital to analog conversion, distortion, filtering, types of microphones, signals capturing processes.

• Sound generators: synthesizers (additive synthesis, subtractive and frequency modulation synthesis…), samplers.

• Computer based recording: capturing of coded sound (sequencers), capturing of sampled sounds (with direct-to-disc recording).

• Standard studio components: mixing consoles, limiters, compressors, reverbs, noise reducers, pitch correction tools, equalizers.

• Protocols and algorithms in computer-based production: MIDI, IEC-60958 (AES / EBU), S/PDIF, AC-3, E-AC-3.

• Synchronization mechanisms: MTC, SMPTE, video, computer games and movies integration.

• Programming standards: interfaces (VST / Steinberg, DirectX / MS), formats (wav, MP3, Ogg), sampled sounds (SoundFont).

• Contemporary sound reproduction (network streaming technology, protocols RTP, RTCP, RTSP), advanced 2D and 3D production (systems 5.1, 7.1, Dolby Atmos).

• Professional tools and their application (Steinberg-Yamaha, Twelve Tone Systems – Roland – BandLab, open-source solutions).

• Latest trends – artificial intelligence and machine learning in sound production (concrete applications of ML in computer sound production).

Addendum: Mini practical tasks covering the latest technological issues or specific issues not covered at laboratory works.

The subject is taught in programs

Objectives and competences

The goal of the course is to educate students (with technological and fine-arts background) for using computers in sound production be it for purely technical, or creative application scenarios and production environments.

General competences:

The ability to define, understand and solve creative professional challenges in computer and information science.
The ability of professional communication in the native language as well as a foreign language.
The ability to understand and apply computer and information science knowledge to other technical and relevant fields (economics, organisational science, fine arts, etc).

Subject specific competences:

Practical knowledge and skills of computer hardware, software and information technology necessary for successful professional work in computer and information science.

Teaching and learning methods

Lectures, laboratory work (with practical prototype implementations), students’ presentations.

Attendance of laboratory work is mandatory (the exact percentage is announced at the beginning of a study year).

The lecturer may impose mandatory attendance of lectures.

Expected study results

After completition of the course a student will:

-be familiar with the engineering principles of computer sound production;

-know and understand physiological laws of sound perception;

-be able to implement these principles in production environments;

-be able to develop basic technological solutions in this area;

-know how to use the acquired knowledge in creative ways (fine arts);

-be familiar with intellectual property protection.

Basic sources and literature

D. Trček: Računalniška zvočna produkcija, kopije prosojnic, FRI UL, 2023 / 2024.
Loy G., Musimathics, The MIT Press, MIT, Cambridge, 2006.
V učnem načrtu omenjeni standardi.