Abstract
In recent years, the rapid advancement of Artificial Intelligence (AI) voice synthesis technologies has raised significant security concerns, as these tools can be misused for fraud, impersonation, and spreading misinformation. The increasing sophistication of voice deepfakes poses a serious threat to societies, such as privacy and communications security, in digital media. The growing challenge demands reliable methods to authenticate voice recordings. In this research, we propose a machine learning based model to detect Turkish AI-generated voice recordings, as there is a lack of research and solutions focused on non-English languages. We introduce a robust model that is capable of accurately classifying voice samples as either AI or human generated. We analyzed the model with many datasets of both human and AI-generated speeches with different qualities. The performance analyses results show that the proposed model recognizes Turkish AI-generated voice with acceptable accuracy for many systems.
| Original language | English |
|---|---|
| Title of host publication | The 6th Joint International Conference on AI, Big Data and Blockchain, AIBB 2025 |
| Editors | Irfan Awan, Muhammad Younas, George Ghinea, Grønli Tor-Morten, Sevil Sen |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 72-82 |
| Number of pages | 11 |
| ISBN (Print) | 9783032047274 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 6th Joint International Conference on AI, Big Data, and Blockchain, AIBB 2025 - Hybrid, Istanbul, Turkey Duration: 19 Aug 2025 → 21 Aug 2025 |
Publication series
| Name | Lecture Notes in Networks and Systems |
|---|---|
| Volume | 1618 LNNS |
| ISSN (Print) | 2367-3370 |
| ISSN (Electronic) | 2367-3389 |
Conference
| Conference | 6th Joint International Conference on AI, Big Data, and Blockchain, AIBB 2025 |
|---|---|
| Country/Territory | Turkey |
| City | Hybrid, Istanbul |
| Period | 19/08/25 → 21/08/25 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Keywords
- Acoustic Features
- Artificial Intelligence
- Audio Classification
- Deepfake Audio
- Media Authentication
- Neural Networks
- Speech Recognition
- Deep Learning
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