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Course unit, curriculum year 2024–2025
COMP.SGN.220

Advanced Audio Processing, 5 cr

Tampere University
Teaching periods
Active in period 3 (1.1.2025–2.3.2025)
Active in period 4 (3.3.2025–31.5.2025)
Course code
COMP.SGN.220
Language of instruction
English
Academic years
2024–2025, 2025–2026, 2026–2027
Level of study
Advanced studies
Grading scale
General scale, 0-5
Persons responsible
Responsible teacher:
Tuomas Virtanen
Responsible teacher:
Annamaria Mesaros
Responsible organisation
Faculty of Information Technology and Communication Sciences 100 %
Coordinating organisation
Computing Sciences Studies 100 %
Core content
  • Acoustic feature extraction and audio classification. Machine learning for audio classification: recurrent neural networks, connectionist temporal classification, convolutional neural networks. Environmental sound classification, music signal analysis and classification, spatial audio
  • Source separation (one channel and multichannel). Time-frequency masking. Deep neural network based and spectrogram factorization based source separation techniques.
  • Microphone array signal processing: beamforming, source localization and tracking.
Learning outcomes
Prerequisites
Compulsory prerequisites
Further information
Learning material
Equivalences
Studies that include this course
Completion option 1
Accepted exercises, project work, and exam.
Completion of all options is required.

Participation in teaching

07.01.2025 27.02.2025
Active in period 3 (1.1.2025–2.3.2025)

Exam

28.02.2025 28.02.2025
Active in period 3 (1.1.2025–2.3.2025)
10.04.2025 10.04.2025
Active in period 4 (3.3.2025–31.5.2025)