Assumed knowledge: It is essential that you are familiar with the sampling theorem, the discrete Fourier transform, random signals, auto- and cross-correlation and frame-by-frame processing. Students who are not confident in their knowledge from previous signal processing courses (especially the topics mentioned) are strongly advised to revise their previous course materials as quickly as possible to avoid difficulties in this course.

This course is about speech enhancement. Different well known and state-of-the-art methods for noise reduction and dereverberation, with one or multiple microphones, are discussed.

The goal of this course is to provide a strong foundation for researchers, engineers, and graduate students who are interested in the problem of signal and speech enhancement.

Relation to other courses
This course is the most advanced course offered by the university on this topic, and serves as an excellent basis from which to commence research in the area. Various aspects of the course bring students up to date with the very latest developments in the field, as seen in recent international conferences and journals. This course builds on Sprach- und Audiosignalverarbeitung (by Prof. Kellermann), and is well complimented by Mensch-Maschine-Schnittstelle (by Prof. Rabenstein), Praxis der Audiodatenkompression (Dr. Grill) and Selected Topics in Perceptual Audio Coding (Prof. Herre), which deal with many other signal processing methods and gives an understanding of human auditory perception (also a key part of speech enhancement) and speech and audio compression techniques.

Title:

Speech Enhancement

Credits: 2,5

Prerequisites

• Signals and Systeme I & II

• Digital Signal Processing