|
|
Voice-enabled healthcare (VEH)- Lecturer
- PD Dr. rer. nat. Björn Heismann
- Details
- Seminar
Präsenz
, ECTS studies, ECTS credits: 2,5
nur Fachstudium, Sprache Deutsch und Englisch
Time and place: Tue 14:15 - 15:45, Seminarraum ZMPT; comments on time and place: Further information will be provided on StudOn
- Fields of study
- WPF MT-MA ab 1
- Prerequisites / Organisational information
- Master-Studenten MT Semester 1-3 (und andere interessierte Fachrichtungen)
- Contents
- Voice recognition, speech synthesis, sentiment analysis and natural language processing are groundbreaking technologies for improved human machine interactions. This seminar intends to give students the opportunity to get in touch with the latest technologies in this space and venture out on a literature review or prototype building journey to improve healthcare applications. The seminar features a lecture part where participants are introduced to the algorithmic background of voice and natural language processing. You are enabled to analyze literature and / or develop own prototypes of voice-enabled healthcare applications. Potential fields of application include e.g. voice-controlled interventional devices and sentiment analysis for psychiatric diseases.
Objectives:
Understand science of voice recognition and natural language processing
Understand medical human interactions and medical needs
Analyze combinations of voice technologies and potential applications in medicine
Skills:
Algorithmic background of voice recognition and NLP
Literature analysis and prototype building
Advanced knowledge: Medical technology
Basic knowledge: Medicine
- ECTS information:
- Credits: 2,5
- Additional information
- Expected participants: 10, Maximale Teilnehmerzahl: 10
www: https://www.studon.fau.de/crs4043631.html
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2022/2023:
- Biomedizin und Hauptseminar Medizintechnik (BuHSMT)
- Voice-enabled healthcare (VEH)
- Department: Chair of Computer Science 5 (Pattern Recognition)
|
|
|