Open Access
Anushka Salunke
Dr. Jagdish.W. Bakal
Punnyai Suryawanshi
Neha Upadhye
- Student Department of Computer Science and Engineering, Pillai Hoc College of Engineering and Technology Maharashtra India
- Principle Department of Computer Science and Engineering, Pillai Hoc College of Engineering and Technology Maharashtra India
- student Department of Computer Science and Engineering, Pillai Hoc College of Engineering and Technology Maharashtra India
- Student Department of Computer Science and Engineering, Pillai Hoc College of Engineering and Technology Maharashtra India
Abstract
The Realtime Voiceover Translation Project stands as a pioneering endeavor poised to reshape the landscape of cross-cultural communication. In response to the escalating demand for fluid interaction amidst linguistic diversity, this initiative sets out to engineer a transformative solution. Its core objective lies in the seamless mediation of language barriers during real-time exchanges. Through the fusion of cutting-edge speech recognition and machine translation technologies, the project endeavors to fabricate a dynamic platform. This platform will possess the remarkable capability to instantaneously transmute spoken utterances into translated textual counterparts. By harnessing the power of sophisticated algorithms, it aims to capture, interpret, and swiftly convert diverse languages into comprehensible text. Subsequently, employing state-of-the-art text-to-speech synthesis, the translated text will be elegantly vocalized, restoring linguistic harmony in the user’s preferred language. The Realtime Voiceover Translation Project harbors immense potential to redefine the boundaries of global interaction, fostering fluid dialogue across linguistic frontiers. Its envisioned impact extends beyond mere convenience, empowering individuals and enterprises alike to engage effortlessly and authentically across linguistic divides. As it navigates the forefront of technological innovation, this project embodies a beacon of inclusivity, heralding a future where language ceases to be a barrier but becomes a bridge to shared understanding and collaboration.
Keywords: Realtime Voiceover Translation Project, Language barriers, real-time communication, Speech Recognition, Machine Translation.
[This article belongs to International Journal of Computer Science Languages(ijcsl)]
References
[1] Wu J, Polyak A, Taigman Y, Fong J, Agrawal P, He Q. Multilingual text-to-speech training using cross language voice conversion and self-supervised learning of speech representations. InICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2022 May 23 (pp. 8017-8021). IEEE.
[2] Gupta AK, Somkunwar R, Kumari A, Kumari A, Godhke K, Repale J. Web based multilingual real time speech transcription transliteration and translation system. In2021 5th International Conference on Information Systems and Computer Networks (ISCON) 2021 Oct 22 (pp. 1-5). IEEE.
[3] Sanchit Chaudhari, Aniket Shukla, Tanvi Gaware, Nehali Shinde. Real Time Direct Speech-to-Speech Translation. International Journal of Advanced Research in Science, Communication and Technology (IJARSCT). 2022;2(3):881-884.
[4] Patel D, Kudalkar M, Gupta S, Pawar R. Real-Time Text & Speech Translation Using Sequence To Sequence Approach. In2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA) 2021 Sep 2 (pp. 722-727). IEEE.
[5] Inaguma H, Duh K, Kawahara T, Watanabe S. Multilingual end-to-end speech translation. In2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) 2019 Dec 14 (pp. 570-577). IEEE.
[6] Gamal Bohouta and Veton Z Këpuska. Real Time Speech Translation (Google TV and Chat). ResearchGate, January 2018
[7] Ping L. Mobile Platform Speech Intelligent Recognition and Translation APP. In2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) 2021 Jan 16 (pp. 595-598). IEEE.
[8] Kim JW, Yoon H, Jung HY. Linguistic-coupled age-to-age voice translation to improve speech recognition performance in real environments. IEEE Access. 2021 Sep 24;9:136476-86.
[9] Krupakar H, Rajvel K, Bharathi B, Deborah SA, Krishnamurthy V. A survey of voice translation methodologies—Acoustic dialect decoder. In2016 International Conference on Information Communication and Embedded Systems (ICICES) 2016 Feb 25 (pp. 1-9). IEEE.
[10] Anna Matamala, Eliana Franco, Voice-over Translation, ResearchGate, January 2010
| Volume | 02 |
| Issue | 01 |
| Received | April 24, 2024 |
| Accepted | April 30, 2024 |
| Published | May 9, 2024 |