Deepfake Voice System for Spoofing
2
Issued Date
2024-01-01
Resource Type
Scopus ID
2-s2.0-85216571430
Journal Title
19th International Joint Symposium on Artificial Intelligence and Natural Language Processing, iSAI-NLP 2024
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SCOPUS
Bibliographic Citation
19th International Joint Symposium on Artificial Intelligence and Natural Language Processing, iSAI-NLP 2024 (2024)
Suggested Citation
Poopradit W., Saebe P., Chinnasri V., Phienthrakul T. Deepfake Voice System for Spoofing. 19th International Joint Symposium on Artificial Intelligence and Natural Language Processing, iSAI-NLP 2024 (2024). doi:10.1109/iSAI-NLP64410.2024.10799251 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/104275
Title
Deepfake Voice System for Spoofing
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Abstract
This paper presents a deep fake voice spoofing system. To develop this system, the concept of a voice modulation system for altering and replicating human voices are explored. Tacotron2, Glow-TTS, and XTTS-V2 are studied, and they demonstrate the significant advancements in voice replication technology. The methodology involves a comprehensive process of audio data collection, and model implementation, followed by integration into a user-friendly website. The evaluation phase employs user acceptance testing with the Mean Opinion Score (MOS) as the primary metric, where participants rate the quality and resemblance of the synthesized voice compared to the original. The results highlight the voice modulator's effectiveness in achieving high-fidelity voice replication, with positive user feedback.