Course: Introduction to Digital Audio Processing

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Course title Introduction to Digital Audio Processing
Course code KI/DZZ
Organizational form of instruction Seminary
Level of course Bachelor
Year of study not specified
Semester Winter
Number of ECTS credits 2
Language of instruction Czech
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Burle Jan, Ing. PhD
Course content
1. Wave nature of sound. Analog vs. digital audio recording, D/A and A/D conversion, sampling and quantization. Audio consequences of aliasing, denormalized numbers (denorms), clipping (hard distortion). Time shift (delay), scaling (multiplication), and mixing (addition) of sounds. - Software: Audacity, Python + libraries (NumPy, Librosa) 2. The human ear, hearing, and sound perception (psychoacoustics). Time and frequency domain of the audio signal. Amplitude and frequency, linear and logarithmic scale, decibel. Spectrogram of the audio signal. Musical and non-musical sounds (tones, noises). Sine waves, harmonic (soft) distortion, harmonic overtone series. - Software: Python, Sonic Visualiser 3. Sound synthesis. Unit generators: oscillators (sine, square, triangle, sawtooth), envelope generators (ADSR), filters, equalizers. Basic methods of sound synthesis: additive, subtractive, modulation, sampling. Noise generators. Synthesizers, Moog, Theremin. - Software: Pure Data, Max/MSP 4. Sound analysis. Short-Time Fourier Transform (STFT), windowing of the signal, interpretation of spectrograms. Lossy and lossless audio compression, specifics of MP3 compression. - Software: Sonic Visualiser, Python 5. Web Audio (HTML5, audio DSP in the browser). - Software: HTML, JavaScript/TypeScript 6. Sound recording. Microphones, their types and characteristics. Stereophony, binaural sound, surround sound, ambisonics. History of recording and playback technologies. 7. Musical sound. Tones, pitch, musical intervals, octave division, chords, harmony, rhythm. Musical instruments and their spectral and temporal characteristics. Sound synthesis of musical instruments. - Software: csound 8. Music programming. Synthesizers and sequencers, MIDI. Software for music applications. Musical interfaces, electronic instruments. Music description languages. Algorithmic music composition. - Software: SuperCollider 9. Speech signal. Specifics of speech signals. Parameter extraction (envelope, pitch, formants, noise). Speech synthesis. 10. Spatial acoustics. Perception of space, acoustic properties of rooms, simulation of sound propagation. Impulse response, convolution, echo, and reverberation. 11. Modern trends in digital audio processing I (AI and machine learning). 12. Modern trends in digital audio processing II (sound design). 13. Current topics.

Learning activities and teaching methods
unspecified
Learning outcomes
The aim of the course is to introduce students to the fundamentals of digital audio processing and its applications. The course is designed to provide a broader overview of the field. Selected theoretical foundations are immediately applied in practice, using Python, JavaScript, and specialized audio processing software. Among other topics, the course also addresses sound perception and the generation of musical audio signals.

Prerequisites
unspecified

Assessment methods and criteria
unspecified
completion of assigned tasks related to the covered material, a seminar project or a literature review, and their presentation during the final colloquium
Recommended literature


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester