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--- |
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license: cc-by-sa-4.0 |
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language: |
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- th |
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tags: |
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- speech-recognition |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: validation |
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path: data/validation-* |
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- split: test |
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path: data/test-* |
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dataset_info: |
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features: |
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- name: audio |
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dtype: |
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audio: |
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sampling_rate: 16000 |
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- name: sentence |
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dtype: string |
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- name: speaker_id |
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dtype: string |
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- name: mic |
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dtype: string |
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- name: duration |
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dtype: float64 |
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splits: |
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- name: train |
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num_bytes: 8212128894.78 |
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num_examples: 120245 |
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- name: validation |
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num_bytes: 1296622162.01 |
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num_examples: 13090 |
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- name: test |
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num_bytes: 1623791447.32 |
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num_examples: 27580 |
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download_size: 13180732521 |
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dataset_size: 11132542504.109999 |
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--- |
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# LOTUSDIS |
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## Dataset Description |
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## How to use |
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You can easily load the dataset using the 🤗 `datasets` library. The dataset can be loaded and prepared with a single line of Python code: |
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```python |
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from datasets import load_dataset |
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lotus_dis = load_dataset("nectec/LOTUSDIS", split="train") |
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``` |
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To iterate through the dataset without downloading it entirely, you can use streaming mode: |
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```python |
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from datasets import load_dataset |
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lotus_dis = load_dataset("nectec/LOTUSDIS", split="train", streaming=True) |
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print(next(iter(lotus_dis))) |
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``` |
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Learn more about how to load and prepare audio datasets in the [Hugging Face Audio Datasets tutorial](https://huggingface.co/blog/audio-datasets). |
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Full meeting session resources: |
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- Audio files: [Download here](https://drive.google.com/file/d/1ofw99Y5W1p8f1DSaIbJkS0xWtuTI2Hrc/view) |
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- Annotation files (TextGrid): [Download here](https://drive.google.com/file/d/14fMv_X_8sGDPGbnU-hpJ85Mug43AHlgO/view) |
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## Citation |
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``` |
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@misc{tipaksorn2025lotusdisthaifarfieldmeeting, |
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title={LOTUSDIS: A Thai far-field meeting corpus for robust conversational ASR}, |
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author={Pattara Tipaksorn and Sumonmas Thatphithakkul and Vataya Chunwijitra and Kwanchiva Thangthai}, |
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year={2025}, |
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eprint={2509.18722}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2509.18722}, |
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} |
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``` |
