Audio source identification based on residual network

Yingqiu Zhang; Da Luo

doi:10.1117/12.2653493

8 December 2022 Audio source identification based on residual network

Yingqiu Zhang, Da Luo

Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 124742P (2022) https://doi.org/10.1117/12.2653493
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China

Abstract

Large number of audio recordings are used in law enforcement and litigation procedures, and it also brings security issues such as the identification of the audio source. This paper mainly studies the problem of source identification (device detection). We proposed an audio source identification framework based on an improved residual network model that introduces a character category output, which will help to improve the identification accuracy for the special case of cross speaker. Experiments show that this audio source identification framework based on residual network has achieved good results under the condition of non-target recognition task, with the highest accuracy rate reaching above 98%, which outperforms the current audio source identification algorithm.

Citation Download Citation

Yingqiu Zhang and Da Luo "Audio source identification based on residual network", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 124742P (8 December 2022); https://doi.org/10.1117/12.2653493

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Performance modeling

3D modeling

Convolution

Fourier transforms

Cell phones

Feature extraction

Show All Keywords

Keywords/Phrases

Search In:

Publication Years