phy696 - Advanced Topics Speech and Audio Processing (Vollständige Modulbeschreibung)
Modulbezeichnung | Advanced Topics Speech and Audio Processing |
Modulkürzel | phy696 |
Kreditpunkte | 6.0 KP |
Workload | 180 h
( Attendance: 56 hrs, Self study: 124 hrs )
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Einrichtungsverzeichnis | Institut für Physik |
Verwendbarkeit des Moduls |
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Zuständige Personen |
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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. |
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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 |
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Gesamtmodul | oral exam (30 minutes) or homework or practical report |
Lehrveranstaltungsform | Vorlesung |
SWS | 4 |
Angebotsrhythmus | SoSe oder WiSe |