Add link to paper and dataset description

README.md

@@ -67,11 +67,30 @@ language:
 - tyv
 - sah
 license: mit
+size_categories:
+- 1M<n<10M
 task_categories:
 - audio-classification
+pretty_name: LRL spoof
 tags:
 - antispoofing
-pretty_name: LRL spoof
-size_categories:
-- 1M<n<10M
----
+---
+
+# LRLspoof: Low-Resource Language Spoofing Corpus
+
+LRLspoof is a large-scale multilingual synthetic-speech corpus designed for cross-lingual spoof detection. 
+
+The dataset was introduced in the paper [When Spoof Detectors Travel: Evaluation Across 66 Languages in the Low-Resource Language Spoofing Corpus](https://huggingface.co/papers/2603.02364).
+
+### Dataset Summary
+
+- **Total Audio:** 2,732 hours
+- **Number of Languages:** 66 (including 45 low-resource languages)
+- **Generation:** Audio was generated using 24 different open-source Text-to-Speech (TTS) systems.
+- **Purpose:** Benchmarking countermeasures for synthetic speech detection (spoofing) across diverse linguistic domains.
+
+### Key Features
+
+* **Multilingual Scope:** Covers a wide variety of languages to evaluate how language-specific features act as a source of domain shift in spoof detection.
+* **Scale:** One of the largest available corpora for synthetic speech detection, facilitating robust training and evaluation.
+* **Low-Resource Focus:** Explicitly includes 45 languages defined as low-resource, addressing a gap in current AI safety and security research.