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Language of instruction
French, English
Teaching content
MO-ST
This course occurs in the following program(s)
Diplôme Ingénieur ISEN (Master's degree in electronics and information technology)
- Crédits ECTS: 0.00
Training officer(s)
A.PATE
Stakeholder(s)
A.PATE
Présentation
Prerequisite
- Signal and image analysis (3rd year)
- Basics of physics (waves and acoustics)
- Scientific computing (e.g. Python or Matlab)
- Basics of physics (waves and acoustics)
- Scientific computing (e.g. Python or Matlab)
Goal
Target competences: 31 (311/313), 32 (321/322/323), 41 (411/413), 111 (1111), 146 (1461), 56 (561/562)
- Get familiar with digital signal processing and filtering through real-life applications in the audio domain (speech and music)
- Know how to describe and analyze an audio signal in the time, spectral, and time-frequency domains
- Know and implement classical audio analysis methods
- As a group, apply and organize acquired knowledge to analyze and understand state-of-the-art methods
- Get familiar with digital signal processing and filtering through real-life applications in the audio domain (speech and music)
- Know how to describe and analyze an audio signal in the time, spectral, and time-frequency domains
- Know and implement classical audio analysis methods
- As a group, apply and organize acquired knowledge to analyze and understand state-of-the-art methods
Presentation
- Basics of acoustics (propagation, atténuation, absorption, reflection, transmission, intensity, sound level, radiation, impulse response, reverberation)
- Time (onset, energy, zero-crossing...) and frequency (fundamental frequency, spectral centroid, ...) signal descriptors
- Detection of fundamental frequency and onset (methods in the time domain, frequency domain, as well as time-frequency domain)
- Speech modeling and coding (source-filter, LPC, cepstrum)
- Time-frequency analysis (STFT, filterbanks)
- Introduction to sound synthesis, denoising, audio coding, audio compression
- Time (onset, energy, zero-crossing...) and frequency (fundamental frequency, spectral centroid, ...) signal descriptors
- Detection of fundamental frequency and onset (methods in the time domain, frequency domain, as well as time-frequency domain)
- Speech modeling and coding (source-filter, LPC, cepstrum)
- Time-frequency analysis (STFT, filterbanks)
- Introduction to sound synthesis, denoising, audio coding, audio compression
Modalités
Forms of instruction
Lecture (10h) - Practical (10h)
Organization
| Type | Amount of time | Comment | |
|---|---|---|---|
| Face to face | |||
| Lectures - face to face | 10,00 | ||
| Lab | 10,00 | ||
| Independent study | |||
| Independent study | 20,00 | ||
| Overall student workload | 40,00 | ||
Evaluation
50% by a written exam
50% mini-project
50% mini-project
| Control type | Duration | Amount | Weighting |
|---|---|---|---|
| Final Exam | |||
| Written test | 2,00 | 1 | 50,00 |
| Defence | 0,50 | 1 | 50,00 |
| TOTAL | 100,00 | ||