Advanced Audio Processing, 5 cr

Tampere University

Teaching periods

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 %

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.