---
license: cc-by-nc-nd-4.0
task_categories:
- automatic-speech-recognition
language:
- en
tags:
- particle-physics
- speech-corpus
- domain-adaptation
- longform
- segments
- manual-transcription
- cern
size_categories:
- 100K<n<1M
dataset_info:
- config_name: longform
  features:
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 48517243701.0
    num_examples: 560
  - name: dev_2020
    num_bytes: 1365959644.0
    num_examples: 14
  - name: dev_2022
    num_bytes: 1104577536.0
    num_examples: 11
  - name: test_2020
    num_bytes: 1581799930.0
    num_examples: 15
  - name: test_2022
    num_bytes: 3155188963.0
    num_examples: 32
  download_size: 52181447847
  dataset_size: 55724769774.0
- config_name: segments
  features:
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 40009686180.696
    num_examples: 174376
  - name: dev_2020
    num_bytes: 1318912292.128
    num_examples: 3896
  - name: dev_2022
    num_bytes: 754694121.774
    num_examples: 3622
  - name: test_2020
    num_bytes: 1672421485.652
    num_examples: 4017
  - name: test_2022
    num_bytes: 2277429244.504
    num_examples: 9738
  download_size: 46780473298
  dataset_size: 46033143324.754
configs:
- config_name: longform
  data_files:
  - split: train
    path: longform/train-*
  - split: dev_2020
    path: longform/dev_2020-*
  - split: dev_2022
    path: longform/dev_2022-*
  - split: test_2020
    path: longform/test_2020-*
  - split: test_2022
    path: longform/test_2022-*
- config_name: segments
  data_files:
  - split: train
    path: segments/train-*
  - split: dev_2020
    path: segments/dev_2020-*
  - split: dev_2022
    path: segments/dev_2022-*
  - split: test_2020
    path: segments/test_2020-*
  - split: test_2022
    path: segments/test_2022-*
---

# LHCP-ASR

This dataset is another version of the [LHCP-ASR](https://www.mllp.upv.es/lhcp-asr) corpus, an English speech dataset for narrow-domain ASR benchmarking in high-energy physics. Unlike the original distribution, which includes video, slides and text data, this version focuses entirely on audio-text pairs

DESCRIPTION
-----------

The speech data are **30 hours** of LHCP plenary conference talks (2020, 2022) with manual (human) verbatim transcriptions and **205 hours** of LHCP conference talks (2020-2022) with automatic verbatim transcriptions (pseudo-labels) for training/adaptation. This version has been released in two formats: `segments` of the talks (less than 30s each) and `longform`, which provides the full talk.

### Data structure
Each sample in the dataset contains:
* `audio`
* `transcription`

USAGE
-----

You can load this dataset directly using the `datasets` library:

```python
from datasets import load_dataset

# Segmented version
segmented_dataset = load_dataset("mllp/LHCP-ASR", "segments")

# Longform version
longform_dataset = load_dataset("mllp/LHCP-ASR", "longform")
````

Both configurations (`longform` and `segments`) include the following splits:
- `train`
- `dev_2020`
- `dev_2022`
- `test_2020`
- `test_2022`

CITATION
--------

If you use this dataset, please cite the original work:

```bibtex
@inproceedings{santamariajorda25_interspeech,
  title     = {{LHCP-ASR: An English Speech Corpus of High-Energy Particle Physics Talks for Narrow-Domain ASR Benchmarking}},
  author    = {Jaume Santamaría-Jordà and Pablo Segovia-Martínez and Gonçal V. {Garcés Díaz-Munío} and Joan Albert Silvestre-Cerdà and Adrià Giménez and Rubén {Gaspar Aparicio} and René {Fernández Sánchez} and Jorge Civera and Albert Sanchis and Alfons Juan},
  year      = {2025},
  booktitle = {{Interspeech 2025}},
  pages     = {4033--4037},
  doi       = {10.21437/Interspeech.2025-2630},
  issn      = {2958-1796},
}
```

For more details on the original dataset, visit [www.mllp.upv.es/lhcp-asr](https://www.mllp.upv.es/lhcp-asr).

LEGAL DISCLAIMER
---------------
Speech and text data were provided by the [European Organization 
for Nuclear Research (CERN)](https://home.cern/) under PO OV9177345.
The following disclaimers are those available in the [CERN Document Server (CDS)](https://cds.cern.ch/) repository on May 30th, 2025:

#### CERN Document Server - Terms and Conditions
[![DOI](https://repository.cern/badge/DOI/10.17181/s2cm2-jaj10.svg)](https://doi.org/10.17181/s2cm2-jaj10)

Use of the CERN Document Server service (hereafter "CDS") denotes agreement with the following terms of use:

* CDS is provided free of charge. It serves as a comprehensive institutional repository and dissemination platform for the research and historical output produced by CERN, the European Organization for Nuclear Research, and its members of personnel. See Content Policy [1] for more details.
* By uploading content to CDS, the content provider affirms that such content complies with all applicable laws, licence conditions and third party rights, and shall hold CERN free and harmless from any related liability.
* All content is provided "as is" and without warranty of any kind. The user shall hold CERN and individual content providers free and harmless from any related liability in connection with its use of such content.
* Users shall respect copyright and all applicable licence conditions. The download and use of content from CDS does not amount to a transfer of intellectual property.
* CERN reserves the right, without notice or liability, and at its sole discretion, to restrict or remove a user's access or remove any uploaded content, where it considers that use of CDS interferes with its operations or violates these Terms and Conditions, and/or applicable laws.
* CERN bases CDS on leading technologies and architectures, operated within the limits of its financial and human resources and made available by CERN on an "as is" and "best efforts" basis. Access to, availability and use of CDS is not guaranteed nor can be expected.
* CERN excludes and disclaims all liability for damage resulting from users' access, or inability to access, or use of CDS.
* These terms and conditions of use are subject to change by CERN at any time and without notice, other than through posting the updated terms on the CDS website. Any revised terms and conditions of use shall become effective immediately upon posting.

If you have any questions or comments with respect to CDS, or if you are unsure whether your intended use is in line with these Terms and Conditions, or if you seek permission for a use that does not fall within these Terms and Conditions, please contact CDS support. 

[1] CDS Content Policy [![DOI](https://repository.cern/badge/DOI/10.17181/8sm4v-js382.svg)](https://doi.org/10.17181/8sm4v-js382)

LICENSE
-------
This dataset is licenced under CC-BY-NC-ND 4.0. To view a copy of this licence, visit https://creativecommons.org/licenses/by-nc-nd/4.0/