Summary of Sing It, Narrate It: Quality Musical Lyrics Translation, by Zhuorui Ye et al.
Sing it, Narrate it: Quality Musical Lyrics Translation
by Zhuorui Ye, Jinhan Li, Rongwu Xu
First submitted to arxiv on: 29 Oct 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 proposes a novel method to translate lyrics for musicals while maintaining high translation quality and singability requirements. The authors develop a three-component framework that includes creating a dataset to train reward models for evaluating translation quality, implementing a two-stage training process with filtering techniques to enhance both singability and translation quality, and introducing an inference-time optimization framework for translating entire songs. Experimental results demonstrate significant improvements over baseline methods and validate the effectiveness of each component in the approach. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper aims to improve song translations for musicals by balancing quality and singability. The authors develop a new method that trains reward models on a dataset, uses two-stage training with filtering, and optimizes translations at inference time. This helps translate lyrics accurately while meeting requirements like length and rhyme. The results show the method outperforms existing approaches. |
Keywords
» Artificial intelligence » Inference » Optimization » Translation
