Abstract
People counting techniques have been widely researched recently and many different types of sensors can be used in this context. In this paper, we propose a system based on a deep-learning model able to identify the number of people in the crowded scenarios through the speech sound. In a nutshell the system relies on two components: counting concurrent speakers in overlapping talking sound directly and clustering single-speaker sound by speaker-identity over time. Compared to previously proposed speaker-counting systems models that only cluster single-speaker sound, this system is more accurate and less vulnerable to the overlapping sound in the crowded environment. In addition, counting speakers in overlapping sound also gives the minimal number of speakers so that it also improves the counting accuracy in a quiet environment. Our methodology is inspired by the newly proposed SincNet deep neural network framework which proves to be outstanding and highly efficient in sound processing with raw signals. By transferring the bottleneck layer of SincNet model as features fed to our speaker clustering model we reached a noticeably better performance than previous models who rely on the use MFCC and other engineered features.
Original language | English |
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Title of host publication | 2020 IEEE International Conference on Pervasive Computing and Communications (PerCom) |
Publisher | IEEE |
Pages | 1 |
Number of pages | 8 |
ISBN (Electronic) | 978-1-7281-4657-7 |
ISBN (Print) | 978-1-7281-4658-4 |
DOIs | |
Publication status | Published - 29 Jun 2020 |
Event | 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom 2020 - University of Austin, Austin, United States Duration: 23 Mar 2020 → 27 Mar 2020 Conference number: 18 http://percom.org/Previous/ST2020/ |
Publication series
Name | Annual IEEE International Conference on Pervasive Computing and Communications (PerCom) |
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Publisher | IEEE |
Volume | 2020 |
ISSN (Print) | 2474-2503 |
ISSN (Electronic) | 2474-249X |
Conference
Conference | 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom 2020 |
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Abbreviated title | PerCom |
Country/Territory | United States |
City | Austin |
Period | 23/03/20 → 27/03/20 |
Internet address |
Keywords
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