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---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
- config_name: release1
data_files:
- split: test
path: release1/test-*
- config_name: release2
data_files:
- split: test
path: release2/test-*
- config_name: release3
data_files:
- split: test
path: release3/test-*
dataset_info:
- config_name: default
features:
- name: WavPath
dtype: string
- name: text
dtype: string
- name: speaker_id
dtype: string
- name: gender
dtype: string
- name: file
dtype: string
- name: id
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
splits:
- name: test
num_bytes: 291284647.45
num_examples: 1155
download_size: 301613803
dataset_size: 291284647.45
- config_name: release1
features:
- name: WavPath
dtype: string
- name: text
dtype: string
- name: speaker_id
dtype: string
- name: gender
dtype: string
- name: file
dtype: string
- name: id
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
splits:
- name: test
num_bytes: 291284647.45
num_examples: 1155
download_size: 301613803
dataset_size: 291284647.45
- config_name: release2
features:
- name: WavPath
dtype: string
- name: text
dtype: string
- name: speaker_id
dtype: string
- name: gender
dtype: string
- name: file
dtype: string
- name: id
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
splits:
- name: test
num_bytes: 291284647.45
num_examples: 1155
download_size: 301613803
dataset_size: 291284647.45
- config_name: release3
features:
- name: WavPath
dtype: string
- name: text
dtype: string
- name: speaker_id
dtype: string
- name: gender
dtype: string
- name: file
dtype: string
- name: id
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
splits:
- name: test
num_bytes: 779194597.212
num_examples: 3737
download_size: 829143229
dataset_size: 779194597.212
---
> 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 tedlium-release1 --model gpt4o_audio
python audio_evals/main.py --dataset tedlium-release2 --model gpt4o_audio
python audio_evals/main.py --dataset tedlium-release3 --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! 🚀 |