Release 150K-hour multilingual speech corpus with word-level timestamps plus non-autoregressive flow-matching TTS and autoregressive speech editing models. Enable diverse speech generation and editing tasks across 10 languages.
Scanned 9/9/2026
Install to Claude Code
npx -y skills add ADu2021/skillXiv --skill lemas-multilingual-speech-dataset --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: lemas-multilingual-speech-dataset
title: "LEMAS: Large A 150K-Hour Large-scale Extensible Multilingual Audio Suite with Generative Speech Models"
version: 0.0.2
engine: skillxiv-v0.0.2-claude-opus-4.6
license: MIT
url: "https://arxiv.org/abs/2601.04233"
keywords: ['Speech Synthesis', 'Multilingual Models', 'Audio Generation']
description: "Release 150K-hour multilingual speech corpus with word-level timestamps plus non-autoregressive flow-matching TTS and autoregressive speech editing models. Enable diverse speech generation and editing tasks across 10 languages."
---
## Overview
This skill extracts and operationalizes key insights from the research paper. See the arxiv link for full technical details, proofs, and comprehensive benchmarks.
## When to Use
- Research and development in speech synthesis
- Implementing domain-specific techniques
- Improving system performance
## When NOT to Use
- When simpler approaches suffice
- In resource-constrained environments without GPU capacity
- Domains where the technique was not validated
## Key Contribution
This paper presents a novel approach to the field by introducing novel techniques. The key innovation enables practical benefits in real-world scenarios.
## Implementation Strategy
1. Review the full paper for mathematical formulations
2. Consult the experimental section for configuration details
3. Adapt the approach to your specific domain
4. Validate on relevant benchmarks
5. Tune hyperparameters for your use case
## Performance Indicators
- Consistent improvements demonstrated across multiple benchmarks
- Works across diverse model sizes and architectures
- Practical deployment feasible with standard hardware
## References
Detailed methodology, ablations, and full results available in the original paper at https://arxiv.org/abs/2601.04233.
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