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Curriculum

Modul CS5260SJ14 T

Module part: Speech and Audio Signal Processing (SprachA14a)

Duration:


1 Semester
Turnus of offer:


normally each year in the summer semester
Credit points:


4
Course of studies, specific field and terms:
  • Master Computer Science 2019 (module part), Module part, Arbitrary semester
  • Master Biophysics 2023 (module part), advanced curriculum, 1st and 2nd semester
  • Master Entrepreneurship in Digital Technologies 2020 (module part), Module part, Arbitrary semester
  • Master Biophysics 2019 (module part), advanced curriculum, 1st or 2nd semester
  • Master IT-Security 2019 (module part), Module part, Arbitrary semester
  • Master Computer Science 2014 (Module part of a compulsory module), Module part, Arbitrary semester
  • Master Entrepreneurship in Digital Technologies 2014 (module part), Module part, Arbitrary semester
  • Master MES 2014 (module part), computer science / electrical engineering, 1st or 2nd semester
Classes and lectures:
  • Speech and Audio Signal Processing (lecture, 2 SWS)
  • Speech and Audio Signal Processing (exercise, 1 SWS)
Workload:
  • 20 Hours exam preparation
  • 45 Hours in-classroom work
  • 55 Hours private studies
Contents of teaching:
  • Speech production and human hearing
  • Physical models of the auditory System
  • Dynamic compression
  • Spectral analysis: Spectrum and Cepstrum
  • Spectral perception and masking
  • Vocal tract models
  • Linear prediction
  • Coding in time and frequency domains
  • Speech synthesis
  • Noise reduction and echo compensation
  • Source localization and spatial reproduction
  • Basics of automatic speech recognition
Qualification-goals/Competencies:
  • Students are able to describe the basics of human speech production and the corresponding mathematical models.
  • They are able to describe the process of human auditory perception and the corresponding signal processing tools for mimicing auditory perception.
  • They are able to present basic knowledge of statistical speech modeling and automatic speech recognition.
  • They can describe and use signal processing methods for source separation and room-acoustic measurements.
Grading through:
  • exam type depends on main module
Responsible for this module:
  • Siehe Hauptmodul
Teachers:
  • Prof. Dr.-Ing. Markus Kallinger
Literature:
  • L. Rabiner, B.-H. Juang: Fundamentals of Speech Recognition - Upper Saddle River: Prentice Hall 1993
  • J. O. Heller, J. L. Hansen, J. G. Proakis: Discrete-Time Processing of Speech Signals - IEEE Press
Language:
  • offered only in German
Notes:

Prerequisites for attending the module:
- None

Prerequisites for the exam:
- Successful completion of assignments during the semester.

Module examination(s):
- see superordinate module

(Is modul part of CS4290, CS4510, RO4290-KP04)
(Is the same as CS5260SJ14)

Letzte Änderung:
8.3.2024