TACNET: Temporal Audio Source Counting Network
November 04, 2023 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Amirreza Ahmadnejad, Ahmad Mahmmodian Darviishani, Mohmmad Mehrdad Asadi, Sajjad Saffariyeh, Pedram Yousef, Emad Fatemizadeh
arXiv ID
2311.02369
Category
cs.SD: Sound
Cross-listed
cs.AI,
cs.LG,
eess.AS
Citations
3
Venue
arXiv.org
Last Checked
3 months ago
Abstract
In this paper, we introduce the Temporal Audio Source Counting Network (TaCNet), an innovative architecture that addresses limitations in audio source counting tasks. TaCNet operates directly on raw audio inputs, eliminating complex preprocessing steps and simplifying the workflow. Notably, it excels in real-time speaker counting, even with truncated input windows. Our extensive evaluation, conducted using the LibriCount dataset, underscores TaCNet's exceptional performance, positioning it as a state-of-the-art solution for audio source counting tasks. With an average accuracy of 74.18 percentage over 11 classes, TaCNet demonstrates its effectiveness across diverse scenarios, including applications involving Chinese and Persian languages. This cross-lingual adaptability highlights its versatility and potential impact.
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