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