Create README.md

README.md

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+---
+license: cc-by-sa-4.0
+task_categories:
+- text-retrieval
+- automatic-speech-recognition
+language:
+- en
+- zh
+tags:
+- spoken-query-retrieval
+- information-retrieval
+- audio-text-retrieval
+- mteb
+- c-mteb
+- robustness
+pretty_name: SQuTR
+size_categories:
+- 10K<n<100K
+---
+
+# SQuTR: A Robustness Benchmark for Spoken Query to Text Retrieval
+
+[![Paper](https://img.shields.io/badge/Paper-Arxiv-red)] IS COMING!
+[![GitHub](https://img.shields.io/badge/GitHub-Repository-blue)](https://github.com/ttoyekk1a/SQuTR-Spoken-Query-to-Text-Retrieval)
+
+**SQuTR** (Spoken Query-to-Text Retrieval) is a large-scale bilingual benchmark designed to evaluate the robustness of information retrieval systems under realistic acoustic perturbations. 
+
+While speech interaction is becoming a primary interface for IR systems, performance often degrades significantly in noisy environments. SQuTR provides a standardized framework featuring **37,317** complex queries across **6 domains**, synthesized with **200 real speakers**, and evaluated under **4 graded noise levels**.
+
+---
+
+## 🌟 Key Features
+
+* **Bilingual & Multi-Domain:** Includes 6 subsets from MTEB and C-MTEB covering Wikipedia, Finance, Medical, and Encyclopedia domains.
+* **High-Fidelity Synthesis:** Generated using **CosyVoice-3** with diverse speaker profiles, totaling **190.4 hours** of audio.
+* **Robustness Evaluation:** Explicitly models four acoustic conditions: **Clean, Low Noise (20dB), Medium Noise (10dB), and High Noise (0dB)**.
+* **MTEB Compatibility:** Follows standard JSONL/BEIR formatting for seamless integration into modern retrieval pipelines.
+
+---
+
+## 💾 How to Use the Dataset
+
+You can download the dataset directly from this Hugging Face repository. To use the evaluation scripts, please refer to our [GitHub Repository](https://github.com/ttoyekk1a/SQuTR-Spoken-Query-to-Text-Retrieval).