Acoustic Source Localization and Speaker Tracking are continuously gaining importance in fields such as human computer interaction, hands-free operation of smart home devices, and telecommunication. A set-up using a Steered Response Power approach in combination with high-end professional microphone capsules is described and the initial processing stages for detection angle stabilization are outlined. The resulting localization and tracking can be improved in terms of reactivity and angular stability by introducing a Convolutional Neural Network for signal/noise discrimination tuned to speech detection. Training data augmentation and network architecture are discussed; classification accuracy and the resulting performance boost of the entire system are analyzed.

Authors: Ziegler, Jonathan D.; Koch, Andreas; Schilling, Andreas
Affiliations: Stuttgart Media University, Stuttgart, Germany; Eberhard Karls University Tübingen, Tübingen, Germany(See document for exact affiliation information.)
AES Convention: 145 (October 2018) Paper Number: 10101
Publication Date: October 7, 2018 Import into BibTeX
Subject: Semantic Audio
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=19827

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