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Course unit, curriculum year 2021–2022
COMP.SGN.220

Advanced Audio Processing, 5 cr

Tampere University
Teaching periods
Active in period 3 (1.1.2022–6.3.2022)
Active in period 4 (7.3.2022–15.5.2022)
Course code
COMP.SGN.220
Language of instruction
English
Academic years
2021–2022, 2022–2023, 2023–2024
Level of study
Advanced studies
Grading scale
General scale, 0-5
Persons responsible
Responsible teacher:
Tuomas Virtanen
Responsible organisation
Faculty of Information Technology and Communication Sciences 100 %
Coordinating organisation
Computing Sciences Studies 100 %
Core content
  • Acoustic feature extraction and audio classification. Automatic speech recognition. Use of temporal information in classification: hidden Markov models, recurrent neural networks, connectionist temporal classification, convolutional neural networks.
  • 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

10.01.2022 27.02.2022
Active in period 3 (1.1.2022–6.3.2022)

Exam

04.03.2022 04.03.2022
Active in period 3 (1.1.2022–6.3.2022)
27.04.2022 27.04.2022
Active in period 4 (7.3.2022–15.5.2022)