Lecture: Audio Processing for the Internet of Things (AIoT) (Summer Term 2023)
- Instructor: Prof. Dr. Nils Peters
- Credits: 2.5 ECTS
- Term: Summer 2023
- Time: Friday 12:15 - 13:45 (1st Lecture: 21.04.2023)
- Format: hybrid lecture, in English
- Location: Am Wolfsmantel 33, Erlangen-Tennenlohe, Room 3R4.04 and via ZOOM. Link and access information for ZOOM meetings can be found at StudOn (see below).
Fri 21.04.2023, Fri 28.04.2023, Fri 05.05.2023, Fri 12.05.2023,
Fri 26.05.2023, Fri 02.06.2023, Fri 09.06.2023, Fri 16.06.2023,
Fri 23.06.2023, Fri 30.06.2023, Fri 07.07.2023, Fri 14.07.2023
- Office Hours: Thu 13:00–14:00 (virtual, use lecture ZOOM link)
- Exam (graded): Oral examination at the end of term. Students must register for examination via Campo
- Examination Dates and Location: To be announced, contact me.
No lecture on Fri 19.05.2023
The lecture will be offered as a hybrid course via ZOOM (i.e. in-person and virtual via Zoom at the same time).
To access the Zoom sessions, you must register via StudOn prior to the first lecture. In StudOn, you will then find Zoom access information.
Virtual participants must have access to a computer capable of running the ZOOM video conferencing software, including a stable internet connection for audio and video transmission.
- Recordings of the lectures may not be provided.
The course focuses on audio and speech processing algorithms within the context of the Internet of Things (IoT).
Reading material recommendations are provided during the lectures.
- Foundation: history, components, current challenges
- Overview of Relevant Wireless Protocols: bandwidth, range, latency, spectrum
- Audio Device Synchronization: NTP, PTP, device orchestration, wireless acoustic sensor networks, asynchronous and event-driven audio sampling
- Acoustic Sensing for Voice User Interfaces: keyword spotting, speech recognition, speaker verification, anti-spoofing
- Acoustic Scene Detection: event detection, scene classification, anomaly detection, sound tagging
- Sound Creation: text-to-speech, sound generative networks
- Data-over-sound: sound-beacon, watermarking, acoustic fingerprint
- Privacy in IoT: edge vs. cloud processing, secure signal processing, federated learning, differential privacy, audio encryption
Before starting this lecture, it is recommended to complete the following FAU courses (or have equivalent knowledge):
- Signals and Systems I & II
- Digital Signal Processing
- Deep Learning, Machine Learning in Signal Processing