Secure Audio Processing: Facial Encryption with Speech Transcription and Translation
This paper enables efficient ways to handle the files by utilizing the Open AI feature of Automatic Speech Recognition (ASR) system that is by Open AI Whisper. This enables secure file handling that can be achieved using Cryptography systems through encryption and decryption. Protecting audio files while ensuring accurate transcription and translation is a critical challenge, especially in applications requiring strict data security. This research focuses on securing speech data against unauthorized access and manipulation by integrating OpenAI Whisper’s Automatic Speech Recognition (ASR) system with encryption techniques. The proposed model applies text, face, and password-based encryption to safeguard files while allowing real-time multilingual transcription and translation. It addresses the Safeguarding of sensitive audio files and efficient speech recognition system from recognition to saving the files and is protected against unauthorized access and tampering of data. The model enhances the efficient extraction of text in the audio and that can be of any language. Whisper supports 99+ languages and provides accurate transcription. The audio file can be Translated into required Language based on the user preference and can be used in Multilingual environment. The utilization of Open AI whisper enables the transcribing and translating of audio in real time. The integration of cryptography techniques with speech recognition and translation systems has significant implications for fields requiring secure handling of audio data, such as healthcare, legal, and financial industries. This paper finds the Secure file handling and translating using cryptographic techniques and face encryption and that can be used in real time to protect sensitive content and without compromising the translation. The findings confirm that incorporating cryptographic methods with ASR improves both data protection and accessibility, making it a viable solution for securely handling sensitive audio content.
Authors
- Pavan Kapanipathi (ORCID: https://orcid.org/0000-0003-0494-3279)
- Kumar Akash (ORCID: https://orcid.org/0000-0003-2807-0943)
- J. R. V. Jeny
- S. Shivaspandana
Institutions
- Vignan's Foundation for Science, Technology & Research (IN)
Publication Details
- Published
- 2025-03-06
- DOI
- https://doi.org/10.1109/icoeca66273.2025.00032
- Primary Topic
- Speech and Audio Processing
- Type
- article
- Field-Weighted Citation Impact
- 0.00