Datasets:
Tasks:
Automatic Speech Recognition
Formats:
parquet
Languages:
Chinese
Size:
10K - 100K
ArXiv:
License:
Update README.md
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README.md
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@@ -89,26 +89,55 @@ This dataset contains 55.53 hours of high-quality speech data collected from 202
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### Dataset Structure
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The dataset is split into three subsets:
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| Split | # Speakers | # Utterances | Duration (hrs) | Avg. Utterance Length (s) |
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| :--------- | :--------: | :----------: | :------------: | :-----------------------: |
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| `train` |
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| `validation` |
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| `test` |
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| **Total** | **
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The dataset file structure is as follows.
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```
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├──
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├──
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speaker_info.xlsx # summary of speaker information
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```
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Each WAV file has a corresponding
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For more details, please refer to our paper [SeniorTalk](https://www.arxiv.org/abs/2503.16578).
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### Dataset Structure
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## Dialogue Dataset
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The dataset is split into two subsets:
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| Split | # Speakers | # Dialogues | Duration (hrs) | Avg. Dialogue Length (h) |
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| :--------- | :--------: | :----------: | :------------: | :-----------------------: |
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| `train` | 182 | 91 | 49.83 | 0.54 |
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| `test` | 20 | 10 | 5.70 | 0.57 |
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| **Total** | **202** | **101** | **55.53** | **0.55** |
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The dataset file structure is as follows.
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```
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dialogue_data/
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├── wav
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│ ├── train/*.tar
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│ └── test/*.tar
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└── transcript/*.txt
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speaker_info.xlsx # summary of speaker information
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```
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Each WAV file has a corresponding TXT file with the same name, containing its annotations.
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For more details, please refer to our paper [SeniorTalk](https://www.arxiv.org/abs/2503.16578).
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## ASR Dataset
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The dataset is split into three subsets:
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| Split | # Speakers | # Utterances | Duration (hrs) | Avg. Utterance Length (s) |
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| :--------- | :--------: | :----------: | :------------: | :-----------------------: |
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| `train` | 162 | 47,269 | 29.95 | 2.28 |
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| `validation` | 20 | 6,891 | 4.09 | 2.14 |
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| `test` | 20 | 5,869 | 3.77 | 2.31 |
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| **Total** | **202** | **60,029** | **37.81** | **2.27** |
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The dataset file structure is as follows.
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```
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sentence_data/
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├── wav
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│ ├── train/*.tar
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│ ├── dev/*.tar
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│ └── test/*.tar
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└── transcript/*.txt
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speaker_info.xlsx # summary of speaker information
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```
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Each WAV file has a corresponding TXT, containing its annotations.
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For more details, please refer to our paper [SeniorTalk](https://www.arxiv.org/abs/2503.16578).
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