# PUCP-Metrix: An Open-source and Comprehensive Toolkit for Linguistic Analysis of Spanish Texts

arXiv: https://arxiv.org/abs/2511.17402 · HTML: https://mlsanity.com/paper/2511.17402/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 33 references that are in the map.
- First posted on arXiv 21 Nov 2025.

## Builds on (most cited first, 10 of 10)

- [XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages](https://mlsanity.com/paper/2106.13822/) (2021)
- [WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization](https://mlsanity.com/paper/2010.03093/) (2020)
- [MLSUM: The Multilingual Summarization Corpus](https://mlsanity.com/paper/2004.14900/) (2020)
- [XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond](https://mlsanity.com/paper/2104.12250/) (2021)
- [MultiEURLEX -- A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer](https://mlsanity.com/paper/2109.00904/) (2021)
- [Stylometric Detection of AI-Generated Text in Twitter Timelines](https://mlsanity.com/paper/2303.03697/) (2023)
- [Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple Domains](https://mlsanity.com/paper/2309.11285/) (2023)
- [PetKaz at SemEval-2024 Task 8: Can Linguistics Capture the Specifics of LLM-generated Text?](https://mlsanity.com/paper/2404.05483/) (2024)
- [NILC-Metrix: assessing the complexity of written and spoken language in Brazilian Portuguese](https://mlsanity.com/paper/2201.03445/) (2021)
- [MultiAzterTest: a Multilingual Analyzer on Multiple Levels of Language for Readability Assessment](https://mlsanity.com/paper/2109.04870/) (2021)

## Abstract (arXiv)

Linguistic features remain essential for interpretability and tasks that involve style, structure, and readability, but existing Spanish tools offer limited coverage. We present PUCP-Metrix, an open-source and comprehensive toolkit for linguistic analysis of Spanish texts. PUCP-Metrix includes 182 linguistic metrics spanning lexical diversity, syntactic and semantic complexity, cohesion, psycholinguistics, and readability. It enables fine-grained, interpretable text analysis. We evaluate its usefulness on Automated Readability Assessment and Machine-Generated Text Detection, showing competitive performance compared to an existing repository and strong neural baselines. PUCP-Metrix offers a comprehensive and extensible resource for Spanish, supporting diverse NLP applications.