TRAVID: An End-to-End Video Translation Framework
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Abstract (arXiv)
In today's globalized world, effective communication with people from diverse linguistic backgrounds has become increasingly crucial. While traditional methods of language translation, such as written text or voice-only translations, can accomplish the task, they often fail to capture the complete context and nuanced information conveyed through nonverbal cues like facial expressions and lip movements. In this paper, we present an end-to-end video translation system that not only translates spoken language but also synchronizes the translated speech with the lip movements of the speaker. Our system focuses on translating educational lectures in various Indian languages, and it is designed to be effective even in low-resource system settings. By incorporating lip movements that align with the target language and matching them with the speaker's voice using voice cloning techniques, our application offers an enhanced experience for students and users. This additional feature creates a more immersive and realistic learning environment, ultimately making the learning process more effective and engaging.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 16 references that are in the map. First posted on arXiv 20 Sep 2023.
Builds on
5 of 16 references.
References · 5
- 2020A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wildcited by 672
- 2020Towards Automatic Face-to-Face Translationcited by 96
- 2020Learning Individual Speaking Styles for Accurate Lip to Speech Synthesiscited by 74
- 2020Tight Integrated End-to-End Training for Cascaded Speech Translationcited by 13
- 2017Face Translation between Images and Videos using Identity-aware CycleGANcited by 2
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Citing papers per year: 2023: 1; 2024: 0; 2025: 1.
2 papers.