|
--- |
|
language: |
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- en |
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license: cc-by-4.0 |
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configs: |
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- config_name: default |
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data_files: |
|
- split: train |
|
path: train/* |
|
- split: dev |
|
path: dev/* |
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- split: test |
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path: test/* |
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dataset_info: |
|
features: |
|
- name: video_path |
|
dtype: string |
|
- name: audio |
|
dtype: audio |
|
- name: sr |
|
dtype: int64 |
|
- name: abstract |
|
dtype: string |
|
- name: language |
|
dtype: string |
|
- name: split |
|
dtype: string |
|
- name: duration |
|
dtype: float64 |
|
- name: conference |
|
dtype: string |
|
- name: year |
|
dtype: string |
|
config_name: default |
|
splits: |
|
- name: train |
|
num_examples: 4000 |
|
- name: dev |
|
num_examples: 885 |
|
- name: test |
|
num_examples: 1431 |
|
tags: |
|
- text |
|
- audio |
|
- video |
|
--- |
|
|
|
# NUTSHELL: A Dataset for Abstract Generation from Scientific Talks |
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|
|
Scientific communication is receiving increasing attention in natural language processing, especially to help researches access, summarize, and generate content. |
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One emerging application in this area is Speech-to-Abstract Generation (SAG), which aims to automatically generate abstracts from recorded scientific presentations. |
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SAG enables researchers to efficiently engage with conference talks, but progress has been limited by a lack of large-scale datasets. |
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To address this gap, we introduce NUTSHELL, a novel multimodal dataset of *ACL conference talks paired with their corresponding abstracts. |
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|
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More informatation can be found in our paper [NUTSHELL: A Dataset for Abstract Generation from Scientific Talks](https://arxiv.org/abs/2502.16942). |
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|
|
|
|
## Dataset Splits |
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|
|
| Split | Number of Examples | |
|
|-------|--------------------| |
|
| train | 4000 | |
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| dev | 885 | |
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| test | 1431 | |
|
|
|
|
|
## Dataset Fields |
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|
|
| **Field** | **Type** | **Description** | |
|
|------------------|-----------------|---------------------------------------------------------------------------------| |
|
| `video_path` | `string` | The video URL to the ACL talk. | |
|
| `audio` | | | |
|
| | - `array` | A `numpy.ndarray` representing the audio signal. | |
|
| | - `sampling_rate` | The sampling rate of the audio. | |
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| `sr` | `int` | The sampling rate of the audio. | |
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| `abstract` | `string` | The abstract of the ACL paper corresponding to the talk. | |
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| `language` | `string` | The language of the videos and audios: English. | |
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| `split` | `string` | The data split to which the entry belongs, such as "train," "dev," or "test." | |
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| `duration` | `float` | The duration of the video/audio content in seconds. | |
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| `conference` | `string` | The name of the conference associated with the dataset entry. | |
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| `year` | `string` | The year of the conference. | |
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|
|
|
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## Citation |
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``` |
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@misc{züfle2025nutshelldatasetabstractgeneration, |
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title={NUTSHELL: A Dataset for Abstract Generation from Scientific Talks}, |
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author={Maike Züfle and Sara Papi and Beatrice Savoldi and Marco Gaido and Luisa Bentivogli and Jan Niehues}, |
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year={2025}, |
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eprint={2502.16942}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2502.16942}, |
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} |
|
``` |