Lecture: Speech Enhancement, Winter Term 2021/2022
- Instructor: Prof. Dr. Emanuël Habets
- Teaching Assistant: Mohamed Elminshawi
- Time: Winter Term 2021/2022, Tuesday's 14:15-15:45
- Place: Zoom Meeting
- Format: Lecture
- Credits: 2,5 ECTS
- Exam (graded): Oral examination at the end of the term
- Flyer: PDF
- The lecture will be offered as an online course via ZOOM.
- Participation in the ZOOM session is only possible for FAU students. The ZOOM access information
for this course will be made available via StudOn. Therefore, you must register via StudOn prior to the first lecture.
- To ensure privacy, participants are not permitted to record the ZOOM sessions. Furthermore, ZOOM links may not be distributed.
- As a technical requirement, all participants must have access to a computer capable of running the ZOOM video conferencing software (as provided by FAU).
- The required material will be made available to the course participants in the following way:
- All FAU students can get an electronic copy of the required reading material.
- The slides used in the lecture are made available as PDF.
- The Jupyter notebooks and audio examples are made available.
For further information, please contact Prof. Dr. Emanuël Habets.
We live in a noisy world! In all applications that are related to speech from hands-free communication, teleconferencing, hearing aids, cochlear implants, to human-machine interfaces such as smart speakers, a speech signal of interest captured by one or more microphones is contaminated by noise and reverberation. Depending on the level of noise and reverberation, the quality and intelligibility of the captured speech can be greatly reduced. Therefore, it is highly desirable, and sometimes even indispensable, to "clean up" the noisy signals using signal processing techniques before storage, transmission or reproduction.
In this course both traditional and deep learning methods for noise reduction and dereverberation, with one or multiple microphones, are discussed.
The goal of this course is to provide a strong foundation for researchers, engineers, and graduate students who are interested in the problem of signal and speech enhancement.
The lecture slides and videos can be downloaded on StudOn.
Jupyter notebooks have been created that go with the exercises. To access them you need to
- Connect to the FAU network (directly or via VPN).
- Access juplab.audiolabs.uni-erlangen.de.
- Login with the provided user account.
- Select Python in “Spawner Options”. Make sure Launch “JupyterLab (beta)” is NOT checked and then click "Spawn".
- Start the Jupyter notebook with the file extension ipynb.
Further audio-related courses offered by the AudioLabs can be found at: