phy696 - Advanced Topics Speech and Audio Processing (Vollständige Modulbeschreibung)

phy696 - Advanced Topics Speech and Audio Processing (Vollständige Modulbeschreibung)

Originalfassung Englisch PDF Download
Modulbezeichnung Advanced Topics Speech and Audio Processing
Modulkürzel phy696
Kreditpunkte 6.0 KP
Workload 180 h
(
Attendance: 56 hrs, Self study: 124 hrs
)
Einrichtungsverzeichnis Institut für Physik
Verwendbarkeit des Moduls
  • Master Engineering Physics (Master) > Schwerpunkt: Acoustics
Zuständige Personen
  • Doclo, Simon (Modulverantwortung)
  • Doclo, Simon (Prüfungsberechtigt)
  • Gerkmann, Timo (Prüfungsberechtigt)
Teilnahmevoraussetzungen
Basic principles of discrete-time signal processing (preferably completed the course Digital Signal Processing). In addition, Matlab programming skills are required.
Kompetenzziele
The students gain in-depth knowledge about speech and audio processing methods and systems. The students gain practical insights by implementing and evaluating these methods for specific speech and audio applications.
Modulinhalte
After reviewing the basic principles of speech processing and statistical signal processing (adaptive filtering, estimation theory), this course covers techniques and underlying algorithms that are essential in many modern-day speech communication and audio processing systems (e.g. mobile phones, hearing aids, headphones): acoustic echo and feedback cancellation, noise reduction, dereverberation, microphone and loudspeaker array processing, active noise control. During the exercises a typical hands-free speech
Literaturempfehlungen
o o J. Benesty, M. M. Sondhi, Y. Huang: Handbook of Speech Processing, Springer, 2008. o P. Vary, R.

J. Benesty, M. M. Sondhi, Y. Huang: Handbook of Speech Processing, Springer, 2008;

P. Vary, R. Martin: Digital Speech Transmission, Wiley, 2006;

P. Loizou: Speech Enhancement: Theory and Practice, CRC Press, 2017;

S. Haykin: Adaptive Filter Theory, Prentice Hall, 2013,

E. Vincent, T. Virtanen, S. Gannot: Audio source separation and speech

Enhancement, Wiley, 2018.
Links
Unterrichtssprache Englisch
Dauer in Semestern 1 Semester
Angebotsrhythmus Modul jährlich
Aufnahmekapazität Modul unbegrenzt
Modulart Wahlpflicht / Elective
Modullevel MM (Mastermodul / Master module)
Lehr-/Lernform Lecture: 2hrs/week, Exercise: 2hrs/week
Vorkenntnisse Basic principles of discrete-time signal processing (preferably completed the course Digital Signal Processing). In addition, Matlab programming skills are required
Prüfung Prüfungszeiten Prüfungsform
Gesamtmodul
oral exam (30 minutes) or homework or practical report
Lehrveranstaltungsform Vorlesung
SWS 4
Angebotsrhythmus SoSe oder WiSe