Advanced Topics in Perceptual Audio Coding [AKADR]

Lecturer:

Jürgen Herre

Details:

Vorlesung, 2 cred.h, graded certificate, ECTS: 2,5, nur Fachstudium

Dates:

every 2. week Fri, 14:30 - 17:45, 3R4.04
Die Veranstaltung findet im Gebäude des Fraunhofer IIS in Tennenlohe, Am Wolfsmantel 33 statt. Es werden jeweils 4 Stunden alle 2 Wochen gegeben.
starting 2.11.2012

Fields of study:

WF EEI-MA 1-4
WF IuK-MA 1-4
WPF SIM-DH 6-10
WF SIM-MA 1-4
WF WING-MA 1-4
WPF WING-DH 6-10
WPF CME-MA ab 3

Prerequisites / Organisational information:

Signale und Systeme I & II
Multimediakommunikation

Music Processing

Lecturer:

Meinard Müller

Details:

Vorlesung, 2 cred.h, graded certificate, credit: 2/2, ECTS: 2,5

Dates:

Mon, 16:15 - 19:15, 3R4.04
8 sessions per term with each session covering 1,5 lectures = 90 + 45 minutes
starting 22.10.2012

Fields of study:

WF WING-MA 1-4
WF CME-MA ab 2
WF SIM-DH 6-10
WF SIM-MA 1-4
WF WING-DH 6-10
WF EEI-MA 1-4
WF IuK-MA 1-4
WF IuK-MA-MMS-EEI 1-4

Keywords:

Audio, Music, Signal Processing, Fourier Transform, Feature Design, Fingerprinting, Beat Tracking, Music Information Retrieval

Speech Enhancement

Lecturer:

Emanuël Habets

Details:

Vorlesung, 2 cred.h, graded certificate, credit: 2/2, ECTS: 2,5

Dates:

Fri, 10:15 - 11:45, 3R4.04
Die Veranstaltung findet im Gebäude des Fraunhofer IIS in Tennenlohe, Am Wolfsmantel 33 statt.

Fields of study:

WF SIM-DH 6-10
WF WING-MA 1-4
WF EEI-MA 1-4
WPF WING-DH 6-10
WF SIM-MA 1-4
WF IuK-MA 1-4
WPF IuK-MA-MMS-EEI 1-4
WPF CME-MA ab 2

Prerequisites / Organisational information:

Pre-requisites: The minimum pre-requisite for the course are Analysis und Lineare Algebra, Signale und Systeme I, Signale und Systeme II and Digitale Signalverarbeitung (or equivalent). The course Sprach- und Audiosignalverarbeitung (by Prof. Kellermann) provides an excellent basis for the Speech Enhancement course and is therefore highly recommended. Knowledge from Statistische Signalverarbeitung (Prof. Kellermann) and/or Stochastische Prozesse (by Prof. Kellermann) is highly desirable.

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.