Meeting Topic: AES SGS Research Colloquium #3: From Algorithmic to Neural Beamforming - Two Approaches to Multichannel Speech Separation in Pro Audio
Moderator Name: Elena Shabalina - d&b audiotechnik GmbH
Speaker Name: Jonathan D. Ziegler - Institute for Visual Computing, University of Tübingen
Other business or activities at the meeting: Q&A session after the talk
Meeting Location: Zoom virtual Meeting
Jonathan's presentation focused on microphone arrays that use beamforming to enhance their output signal by manipulating and combining the individual sensor signals. He analyzed an algorithmic and machine learning approach for different microphone array configurations. Under laboratory conditions and in practical applications, he examined the tracking performance, which he also made audible to the audience through several audio examples. For more complex applications, he developed a neural network beamforming approach. Jonathan explained the basic network architecture and highlighted advantages of this method. In addition, various aspects of the usability of the approaches in different applications were emphasized.
We thank Jonathan for a very impressive talk with a professional and well understandable presentation of this complex topic. We wish him all the best for his PhD defense.
A recording of the presentation is available on YouTube.
More information about Jonathan's work.
Neural Beamformer Companion Page with audio examples:
Schoeps Project Companion Page:
For more information about the event, please have a look on our section blog post.
Written By: Tobias Goldmann