Summary of Transvip: Speech to Speech Translation System with Voice and Isochrony Preservation, by Chenyang Le et al.
TransVIP: Speech to Speech Translation System with Voice and Isochrony Preservation
by Chenyang Le, Yao Qian, Dongmei Wang, Long Zhou, Shujie Liu, Xiaofei Wang, Midia Yousefi, Yanmin Qian, Jinyu Li, Sheng Zhao, Michael Zeng
First submitted to arxiv on: 28 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Sound (cs.SD); Audio and Speech Processing (eess.AS)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces a novel model framework called TransVIP for end-to-end speech-to-speech translation, which leverages diverse datasets and joint probability to facilitate direct translation. The model is designed to preserve speaker voice characteristics and isochrony from the source speech during translation. Compared to current state-of-the-art models, TransVIP outperforms them on French-English language pair benchmarks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper creates a new way for computers to translate spoken languages directly into other spoken languages. Most previous attempts at this have used multiple steps and separate processes, but this new approach combines all these steps into one model called TransVIP. The model is good at keeping the original speaker’s voice and rhythm in the translated speech. It even beats current best models on translating French to English. |
Keywords
» Artificial intelligence » Probability » Translation
