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metadata
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.

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}, 
}