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README.md

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-LEMAS: A 150K-Hour Large-scale Extensible Multilingual Audio Suite with Generative Speech Models
+# LEMAS: A 150K-Hour Large-scale Extensible Multilingual Audio Suite with Generative Speech Models
 
-We present LEMAS-Dataset, which, to our knowledge, is currently the largest open-source multilingual speech corpus with word-level timestamps. Covering over 150,000 hours across 10 major languages, LEMAS-Dataset is constructed via a efficient data processing pipeline that ensures high-quality data and annotations. To validate the effectiveness of LEMAS-Dataset across diverse generative paradigms, we train two benchmark models with distinct architectures and task specializations on this dataset. LEMAS-TTS, built upon a non-autoregressive flow-matching framework, leverages the dataset's massive scale and linguistic diversity to achieve robust zero-shot multilingual synthesis. Our proposed accent-adversarial training and CTC loss mitigate cross-lingual accent issues, enhancing synthesis stability. Complementarily, LEMAS-Edit employs an autoregressive decoder-only architecture that formulates speech editing as a masked token infilling task. By exploiting precise word-level alignments to construct training masks and adopting adaptive decoding strategies, it achieves seamless, smooth-boundary speech editing with natural transitions. Experimental results demonstrate that models trained on LEMAS-Dataset deliver high-quality synthesis and editing performance, confirming the dataset's quality. We envision that this richly timestamp-annotated, fine-grained multilingual corpus will drive future advances in prompt-based speech generation systems.
+[LEMAS](https://lemas-project.github.io/LEMAS-Project/) is a large-scale extensible multilingual audio suite, providing the largest open-source multilingual speech corpus with word-level timestamps to our knowledge, covering over 150,000 hours across 10 major languages. Built with a rigorous alignment and confidence-based filtering pipeline, LEMAS supports diverse generative paradigms including zero-shot multilingual synthesis (LEMAS-TTS) and seamless speech editing (LEMAS-Edit).
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+<details><summary>Citation</summary>
+  
+@article{zhao2026lemas,
+  title={LEMAS: A 150K-Hour Large-scale Extensible Multilingual Audio Suite with Generative Speech Models},
+  author={Zhao, Zhiyuan and Lin, Lijian and Zhu, Ye and Xie, Kai and Liu, Yunfei and Li, Yu},
+  journal={arXiv preprint arXiv:2601.04233},
+  year={2026}
+}