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README.md

@@ -1,29 +1,45 @@
----
-dataset_info:
-  features:
-  - name: answer
-    sequence: string
-  - name: question
-    dtype: string
-  - name: question_id
-    dtype: string
-  - name: save_name
-    dtype: string
-  - name: WavPath
-    dtype: string
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 16000
-  splits:
-  - name: test
-    num_bytes: 365647954.552
-    num_examples: 1024
-  download_size: 364171436
-  dataset_size: 365647954.552
-configs:
-- config_name: default
-  data_files:
-  - split: test
-    path: data/test-*
----
+
+![logo.png](assets/logo.png)
+
+
+> This dataset only contains test data, which is integrated into UltraEval-Audio(https://github.com/OpenBMB/UltraEval-Audio) framework.
+
+```shell
+python audio_evals/main.py --dataset triviaqa.yaml --model gpt4o_audio
+
+python audio_evals/main.py --dataset triviaqa.yaml --model gpt4o_audio
+```
+
+
+### 🚀超凡体验，尽在UltraEval-Audio🚀
+
+UltraEval-Audio——全球首个同时支持语音理解和语音生成评估的开源框架，专为语音大模型评估打造，集合了34项权威Benchmark，覆盖语音、声音、医疗及音乐四大领域，支持十种语言，涵盖十二类任务。选择UltraEval-Audio，您将体验到前所未有的便捷与高效：
+
+- **一键式基准管理 📥**：告别繁琐的手动下载与数据处理，UltraEval-Audio为您自动化完成这一切，轻松获取所需基准测试数据。
+- **内置评估利器 ⚙️**：无需再四处搜寻评估工具，UltraEval-Audio内置八种常用的评估方法（如WER、WER-ZH、BLEU、G-Eval），无论是基于规则还是模型驱动，都能满足您的需求。
+- **功能强大，灵活易用 🛠️**：支持预览测试、随机样本、错误重试、断点重跑等功能，确保评估过程灵活可控，提升效率与准确性。
+- **无缝集成自定义数据集 💼**：不仅支持公开benchmark，还提供强大的自定义数据集功能，让您在各种工程场景下也能迅速应用。
+- **轻松对接现有系统 🔗**：具备优秀的扩展性和标准化设计，即使您已拥有一套完善的评估体系，UltraEval-Audio也能无缝对接，简化项目管理流程，输出结果统一规范。
+
+
+# UltraEval-Audio: 🎙️ Open-Source Speech Model Evaluation Framework, Empowering Your AI Voice Research!
+
+## One-Stop Evaluation, Time-Saving and Effortless! 🚀
+
+UltraEval-Audio integrates **30+ benchmarks**, covering *speech*, *sound*, *medicine*, *music* four major domains, supporting **10 languages**, and encompassing **12 types of tasks**, helping you easily master speech evaluation!
+
+##  No Tedious Operations, Ready to Use Out of the Box! 🎁
+
+- Automatic Download and Management of Benchmarks, Say Goodbye to Manual Download and Processing! 📥
+- Built-in 8 Common Evaluation Methods, Including **wer, wer-zh, G-Eval**, Meeting Your Diverse Evaluation Needs! 🛠️
+
+## Flexible Expansion, Seamless Integration! 🔗
+
+- Quick Integration of Internal Datasets, Custom Dataset Functionality, Making Your Evaluation More Targeted! 📊
+- Easy Access to Existing Evaluation Systems, Excellent Scalability and Standardization, Allowing UltraEval-Audio to Easily Integrate into Your Evaluation Ecosystem! 🧩
+
+
+Experience Now: https://github.com/OpenBMB/UltraEval-Audio 🌐
+
+
+UltraEval-Audio: 🎙️ Your Best Partner in AI Voice Research, Accelerating Your Breakthroughs in Speech Technology! 🚀