Datasets:
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task_categories:
- translation
language:
- ja
- zh
tags:
- translation
- ja
- zh_cn
dataset_info:
features:
- name: audio
dtype: audio
- name: duration
dtype: float64
- name: sentence
dtype: string
- name: uid
dtype: string
- name: group_id
dtype: string
splits:
- name: train
num_bytes: 2072186696.0
num_examples: 8000
- name: valid
num_bytes: 259808873.0
num_examples: 1000
- name: test
num_bytes: 252154427.0
num_examples: 1000
download_size: 2596980172
dataset_size: 2584149996.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
- split: test
path: data/test-*
---
# ScreenTalk_JA2ZH-XS
**ScreenTalk_JA2ZH-XS** is a paired dataset of **Japanese speech and Chinese translated text** released by DataLabX. It is designed for training and evaluating speech translation (ST) and multilingual speech understanding models. The data consists of spoken dialogue extracted from real-world Japanese movies and TV shows.
## 📦 Dataset Overview
- **Source Language**: Japanese (Audio)
- **Target Language**: Simplified Chinese (Text)
- **Number of Samples**: 10,000
- **Total Duration**: ~30 hours
- **Format**: Parquet
- **License**: CC BY 4.0
- **Tasks**:
- Speech-to-Text Translation (ST)
- Multilingual ASR+MT joint modeling
- Japanese ASR with Chinese aligned text training
## 📁 Data Fields
| Field Name | Type | Description |
|-------------|----------|--------------------------------------------|
| `audio` | `Audio` | Raw Japanese speech audio clip |
| `sentence` | `string` | Corresponding **Simplified Chinese text** |
| `duration` | `float` | Duration of the audio in seconds |
| `uid` | `string` | Unique sample identifier |
| `group_id` | `string` | Grouping ID (e.g., speaker or scene tag) |
## 🔍 Example Samples
| audio | Duration (s) | sentence |
|-----------|---------------|--------------------------------------------|
| JA_00012 | 4.21 | 他不会来了。 |
| JA_00038 | 6.78 | 为什么你会这样说？告诉我真相。 |
| JA_00104 | 3.33 | 安静，有人来了。 |
## 💡 Use Cases
This dataset is ideal for:
- 🎯 Training **speech translation models**, such as [Whisper ST](https://huggingface.co/docs/transformers/main/en/model_doc/whisper#speech-translation)
- 🧪 Research on **multilingual speech understanding**
- 🧠 Developing multimodal AI systems (audio → Chinese text)
- 🏫 Educational tools for Japanese learners
## 📥 Loading Example (Hugging Face Datasets)
```python
from datasets import load_dataset
ds = load_dataset("DataLabX/ScreenTalk_JA2ZH-XS", split="train")
```
## 📃 Citation
```
@misc{datalabx2025screentalkja,
title = {DataLabX/ScreenTalk_JA2ZH-XS: A Speech Translation Dataset of Japanese Audio and Chinese Text},
author = {DataLabX},
year = {2025},
howpublished = {\url{https://huggingface.co/datasets/DataLabX/ScreenTalk_JA2ZH-XS}},
}
```
---
We welcome feedback, suggestions, and contributions! 🙌
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