Summary of Fasst: Fast Llm-based Simultaneous Speech Translation, by Siqi Ouyang and Xi Xu and Chinmay Dandekar and Lei Li
FASST: Fast LLM-based Simultaneous Speech Translation
by Siqi Ouyang, Xi Xu, Chinmay Dandekar, Lei Li
First submitted to arxiv on: 18 Aug 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| 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 proposes a new method called FASST (Fast Large Language Model-based Simultaneous Speech Translation) that can translate speech in real-time while maintaining high quality and low latency. The approach uses blockwise-causal speech encoding and consistency masks to incrementally encode streaming speech input without recomputation, allowing for faster translation. A two-stage training strategy is also developed to optimize FASST for simultaneous inference. The method is evaluated on the MuST-C dataset and outperforms previous state-of-the-art models in terms of quality-latency trade-off. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper creates a new way to translate speech that’s fast and good. It uses special tricks to quickly understand what someone is saying, even if they’re talking really fast. This helps the translation happen faster too! They tested it on some sample talks and found out it worked better than other methods for translating English into Spanish. |
Keywords
» Artificial intelligence » Inference » Large language model » Translation
