Author
Listed:
- Pragati Jain
- Poorvi Ujjainia
- Anshika Srivastava
- Kajal Shrivastav
- Ishu Rani
- Akshat Vashisht
- Rudranarayan Behera
- Bhavika Moza
- Debhjit Mukherjee
Abstract
Modern internet has given rise to various voice related crimes worldwide, notably deepfake voice scams where the perpetrators utilize artificial intelligence to deceive victims by the means of forgery of voice. This review article aims to discuss the advancements and challenges in voice biometrics, particularly focusing on the impact of AI and deep learning on this field. It underscores the evolution of voice biometrics from early methods to modern AI enhanced techniques, by highlighting the significant improvements in accuracy, security, and adaptability etc. The key findings of the article have highlighted that while AI-driven advancements have addressed many challenges including voice robustness and multilingual recognition, new threats like deep fake audio require ongoing innovation. The integration of various methods like deep learning, neural networks and advanced feature extraction has shown incredible potential in enhancing the system resilience. But challenges such as voice variability, privacy concerns and the forensic applications of these technologies remain critical issue to be addressed by the future researchers. This review article recommends multidisciplinary research to bridge the gap between this field and forensic science, emphasizing the need for continued development to address and prevent emerging threats very efficiently.
Suggested Citation
Pragati Jain & Poorvi Ujjainia & Anshika Srivastava & Kajal Shrivastav & Ishu Rani & Akshat Vashisht & Rudranarayan Behera & Bhavika Moza & Debhjit Mukherjee, 2024.
"Forensic Perspective on Voice Biometrics and AI : A Review,"
International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 11(5), pages 49-63, October.
Handle:
RePEc:etm:ijsrst:v11:y2024:i5:id:317
DOI: 10.32628/IJSRST2411581
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:etm:ijsrst:v11:y2024:i5:id:317. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pankaj Sharma (email available below). General contact details of provider: https://ijsrst.com/home .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.