Machine Learning for Signal Processing: EE603A (Fall 2022)

Vipul Arora
Department of Electrical Engineering, IIT Kanpur

⚠ The focus will be on AUDIO signals

TAs:

Vikas - kvikas@
Sumit - krsumit@
Adhiraj - adhiraj@
Arkaprava - arkapravab20@
Thishyan - thishyan20@
Raviteja - rraja21@

Course Objectives:

This course aims at introducing the students to machine learning (ML) techniques used for various signal processing applications. There will be spectral processing techniques for analysis and transformation of audio signals. The lectures will focus on mathematical principles, and there will be coding based assignments for implementation. Prior exposure to ML is not required. The course will be focused on applications in audio signal processing, and the theory will be tailored towards that end.

Pre-requisites:

The course will need a strong background in linear algebra and probability theory.

Topics:

Plagiarism Penalty:
As heavy as possible. Zero-tolerance policy.

References:

This course will take excerpts from some standard books on machine learning and signal processing. But it will largely be based on articles and research papers in ML and SP conferences (e.g., ICASSP, NeurIPS, ICML, Interspeech, ISMIR, etc.) and journals (e.g., IEEE TASLP, JMLR, IEEE PAMI, etc.).

Books:

Articles: