After successful completion of the course, students are able to explain basics in acoustic signal processing, auditory scene analysis, and music information retrieval, implement and apply current techniques in these areas, critically evaluate methods, and—based on this—develop new methods.
Selected topics from the areas of acoustic signal processing, auditory scene analysis, and music information retrieval are presented and discussed, comprising the following:
- Fundamentals of audio processing, analysis, and description
- Audio event detection and classification
- Detection and tracking of musical events
- Tracking of musical concepts (e.g., beats, meter, key)
- Instrument detection and transcription
- Real-time tracking of audio events
- Music genre classification and tagging
- Multi-modality in semantic music description
- Music retrieval and recommendation
Topics are contextualized historically, giving an overview of the development from hand-crafted features to recent deep learning based methods, including convolutional and recurrent neural networks. Emphasis is given to aspects of evaluation, such as used metrics and ground truth construction. Understanding of theoretical concepts is deepened through accompanying applied lab exercises.
