Abstract
This paper presents a complex-valued deep neural network for sound source localization. Most neural network-based sound source localization approaches use time-frequency domain features. Even though both magnitude and phase play a pivotal role in solving the sound source localization problem, the real-valued features are only used because the neural network structures generally accept real-valued inputs only. In contrast, the complex-valued neural network structures directly receive complex-valued inputs and extract complex-valued hidden features. Therefore, the complex-valued deep neural network, which is proposed in this paper, has the potential to extract rich features for sound source localization. With a series of experiments, the proposed direction of arrival estimation method with a complex-valued deep neural network outperforms the real-valued deep neural network-based method.
| Original language | English |
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| Title of host publication | 2024 IEEE International Conference on Consumer Electronics, ICCE 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9798350324136 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 2024 IEEE International Conference on Consumer Electronics, ICCE 2024 - Las Vegas, United States Duration: 2024 Jan 6 → 2024 Jan 8 |
Publication series
| Name | Digest of Technical Papers - IEEE International Conference on Consumer Electronics |
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| ISSN (Print) | 0747-668X |
| ISSN (Electronic) | 2159-1423 |
Conference
| Conference | 2024 IEEE International Conference on Consumer Electronics, ICCE 2024 |
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| Country/Territory | United States |
| City | Las Vegas |
| Period | 24/1/6 → 24/1/8 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- complex-valued deep neural network
- direction-of-arrival estimation
- sound source localization
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering