---
pretty_name: Claire English Dialogue Dataset (CEDD)
license: cc-by-nc-sa-4.0
language:
  - en
multilinguality:
  - monolingual
size_categories:
  - 100M<n<1B
task_categories:
  - text-generation
  - text2text-generation
task_ids:
  - language-modeling
  - dialogue-modeling
  - dialogue-generation
tags:
  - conversational
  - text-generation
  - conditional-text-generation
  - dialogue-modeling
  - dialogue-generation
viewer: true
configs:
- config_name: default
  sample_by: paragraph
  data_files:
  - split: train
    path: "EN/*/train.txt"
  - split: test
    path: "EN/*/test.txt"
---


# Claire English Dialogue Dataset (CEDD) <br />*A collection of English dialogue transcripts*

This is the first packaged version of the datasets used to train the english variants of the Claire family of large language models
([OpenLLM-France/Claire-7B-EN-0.1](https://huggingface.co/OpenLLM-France/Claire-7B-EN-0.1)).

The Claire English Dialogue Dataset (CEDD) is a collection of transcripts of English dialogues from various sources, including parliamentary proceedings, interviews, broadcast, meetings, and free conversations.
Each dialogue is split into speech turns, and each speech turn is labeled with the name of the speaker, or a unique identifier if the speaker is unknown.

* [Dataset composition](#dataset-composition)
  * [Data sources](#data-sources)
* [Example use (python)](#example-use-python)
* [Important notes](#important-notes)
* [License](#license)
* [Citations](#citations)
* [Contact](#contact)


## Dataset composition

CEDD can be broken down into:
* 962550 conversations in total (812705 in train, 11992 in test)
* 20863917 speech turns in total (18576327 in train, 359527 in test)
* around 864M words

It is a collection of several independent datasets, classified by the types of conversations they contain. This categorization is designed to more evenly balance the influence of different styles of dialogue on model training and to facilitate future applications of CEDD for which certain types of dialogue might be more helpful than others.

For more information, you can look at the following documents:
* [EN/metadata.csv](EN/metadata.csv) contains further statistics on the different subcorpora (broken down by train/test splits).
<!-- * XXX -->

### Data sources

<table>
<thead>
<tr>
  <th>Dataset</th>
  <th>Description</th>
  <th>Words</th>
  <th>Turns</th>
  <th>Conversations</th>
  <th>License (and conditions)</th>
</tr>
</thead>
<tbody>
<tr>
  <td colspan="6"><h4>Parliamentary Proceedings</h4></td></tr>
<tr>
  <td><a href="https://www.statmt.org/europarl/">Europarl</a></td>
  <td>The Europarl parallel corpus</td>
  <td>56M</td>
  <td>-</td>
  <td>11K</td>
  <td>No copyright restrictions. If you use this data in your research, please contact phi@jhu.edu</td>
</tr>
<tr>
  <td colspan="6"><h4>Spoken Dialogue</h4></td></tr>
<tr>
  <td><a href="https://anc.org/data/oanc/contents/#charlotte">Charlotte Narratives</a></td>
  <td>The Charlotte Narrative and Conversation Collection (CNCC) contains 95 narratives, conversations and interviews representative of the residents of Mecklenburg County, North Carolina and surrounding North Carolina communities.</td>
  <td>200K</td>
  <td>-</td>
  <td>93</td>
  <td><a href="[https://anc.org/data/oanc/contents/#charlotte](https://anc.org/data/oanc/contents/#charlotte](https://anc.org/data/oanc/download/)">Available for download and use for research and development, including commercial development.</a></td>
</tr>
<tr>
  <td><a href="https://anc.org/data/oanc/contents/#switchboard">Switchboard</a></td>
  <td>The corpus consists of approximately 260 hours of speech and was originally collected by Texas Instruments in 1990-1, under DARPA sponsorship.</td>
  <td>3M</td>
  <td>-</td>
  <td>2320</td>
  <td><a href="https://catalog.ldc.upenn.edu/LDC97S62">LDC User Agreement for Non-Members</a></td>
</tr>
   
<tr>
  <td colspan="6"><h4>Broadcast</h4></td></tr>
<tr>
  <td><a href="https://huggingface.co/datasets/ccdv/mediasum">MediaSum</a></td>
  <td>MediaSum dataset for summarization</td>
  <td>720M</td>
  <td>-</td>
  <td>458K</td>
  <td><a href="https://github.com/zcgzcgzcg1/MediaSum">For research purposes only</a></td>
</tr>

<tr>
  <td colspan="6"><h4>Meetings</h4></td></tr>
<tr>
  <td><a href="https://groups.inf.ed.ac.uk/ami/corpus/">AMI</a></td>
  <td>The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings.</td>
  <td>712K</td>
  <td>-</td>
  <td><1K</td>
  <td><a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></td>
</tr>
<tr>
  <td><a href="https://groups.inf.ed.ac.uk/ami/icsi/">ICSI</a></td>
  <td>About 70 hours of meeting recordings.</td>
  <td>804K</td>
  <td>-</td>
  <td><1K</td>
  <td><a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></td>
</tr>

<tr>
  <td colspan="6"><h4>Assistance</h4></td></tr>
<tr>
  <td><a href="https://redialdata.github.io/website/">ReDial</a></td>
  <td>ReDial (Recommendation Dialogues) is an annotated dataset of dialogues, where users recommend movies to each other.</td>
  <td>1.6M</td>
  <td>-</td>
  <td>-</td>
  <td><a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></td>
</tr>
<tr>
  <td><a href="https://github.com/facebookresearch/opendialkg">OpenDialKG</a></td>
  <td>OpenDialKG is a dataset of conversations between two crowdsourcing agents engaging in a dialog about a given topic.</td>
  <td>1M</td>
  <td>-</td>
  <td>-</td>
  <td><a href="https://creativecommons.org/licenses/by-nc/4.0/legalcode">CC-BY-NC-4.0</a></td>
</tr>
<tr>
  <td><a href="https://github.com/asappresearch/abcd">ABCD</a></td>
  <td>Action-Based Conversations Dataset.</td>
  <td>1.5M</td>
  <td>-</td>
  <td>-</td>
  <td><a href="https://github.com/asappresearch/abcd/blob/master/LICENSE">MIT</a></td>
</tr>
<tr>
  <td><a href="https://github.com/google/airdialogue">AirDialogue</a></td>
  <td>AirDialogue is a benchmark dataset for goal-oriented dialogue generation research.</td>
  <td>37M</td>
  <td>-</td>
  <td>-</td>
  <td><a href="https://github.com/google/airdialogue/blob/master/LICENSE">Apache License 2.0</a></td>
</tr>
<tr>
  <td><a href="https://huggingface.co/datasets/pfb30/multi_woz_v22">MULTIWOZ2_2</a></td>
  <td>Multi-Domain Wizard-of-Oz dataset (MultiWOZ), a fully-labeled collection of human-human written conversations spanning over multiple domains and topics.</td>
  <td>1.9M</td>
  <td>-</td>
  <td>-</td>
  <td><a href="https://choosealicense.com/licenses/apache-2.0/">Apache License 2.0</a></td>
</tr>
<tr>
  <td><a href="https://github.com/awslabs/multi-domain-goal-oriented-dialogues-dataset">MulDoGO</a></td>
  <td>Conversations from the airline, fastfood, finance, insurance, media, and software domains.</td>
  <td>10M</td>
  <td>-</td>
  <td>-</td>
  <td><a href="https://github.com/awslabs/multi-domain-goal-oriented-dialogues-dataset/blob/master/LICENSE.txt">CDLA Permissive License</a></td>
</tr>

<tr>
  <td colspan="6"><h4>Free Chat</h4></td></tr>
<tr>
  <td><a href="https://github.com/BYU-PCCL/chitchat-dataset">Chit-Chat</a></td>
  <td>Open-domain conversational dataset from the BYU Perception, Control & Cognition lab's Chit-Chat Challenge.</td>
  <td>2.3M</td>
  <td>7.1K</td>
  <td>258K</td>
  <td><a href="https://github.com/BYU-PCCL/chitchat-dataset/blob/master/LICENSE">MIT License</a></td>
</tr>
<tr>
  <td><a href="https://huggingface.co/datasets/li2017dailydialog/daily_dialog">DailyDialog</a></td>
  <td>High-quality multi-turn dialog dataset.</td>
  <td>1.2M</td>
  <td>-</td>
  <td>13K</td>
  <td><a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a></td>
</tr>


<tr>
  <td colspan="6"><h4>Misc</h4></td></tr>
<tr>
  <td><a href="">British National Corpus (BNC)</a></td>
  <td>Collection of samples of written and spoken language from a wide range of sources, designed to represent a wide cross-section of British English, both spoken and written, from the late twentieth century.</td>
  <td>110M</td>
  <td>-</td>
  <td>1K</td>
  <td><a href="http://www.natcorp.ox.ac.uk/docs/licence.html">BCN License</a></td>
</tr>

</tbody>
</table>



## Example use (python)

In the following `sample_by="paragraph"` is important to ensure that each sample corresponds to a full conversation (not just a speech turn).

Load dataset from HuggingFace cache (downloaded under `~/.cache/huggingface/datasets`):
```python
from datasets import load_dataset

dataset = load_dataset("OpenLLM-France/Claire-Dialogue-English-0.1", sample_by="paragraph", streaming=True)
```

Load dataset from raw text files:
```python
from datasets import load_dataset
import glob

path = "path/to/dataset"
train_files = glob.glob(path + "/*/train.txt")
test_files = glob.glob(path + "/*/test.txt")

dataset = load_dataset("text", data_files={"train": train_files, "test": test_files}, sample_by="paragraph", streaming=True)
```

Iterate on the dataset:
```python
for sample in dataset["train"]:
    train_conversation = sample["text"]
    ...

for sample in dataset["test"]:
    test_conversation = sample["text"]
    ...
```


## Important notes

All datasets were normalized in text files so that:
* Conversations are separated by a single blank line.
* Each line corresponds to a single speech turn.
* Each line begins with a speaker label of the form "`[***:]`".
* When speaker names are anonymized or otherwise unknown, speakers are distinguished by numbers in the following format: "**`[speaker001:]`**", "**`[speaker002:]`**", … <br /> Otherwise, speakers are labeled with their names or roles, e.g. "`[Paul:]`", "`[François Mitterrand:]`", "`[M. le président:]`".
* There are no parentheses: special annotations are always between square brackets.
* Commong tags include:
    * "**`[PII]`**": Personally Identifiable Information (anonymized name...)
    * "`[NOISE]`": distinct ambient noises
    * "`[LAUGHTER]`": laughter
<!-- * Truncated words are sometimes marked with "-" (ex: "je suis dé- décidé") -->
* Depending on the data source, data may or may not include punctuation marks and upper case letters.
* The data were normalized in various ways including unicode NFC normalization, conversion of unbreakable spaces to spaces, and standardization of punctuation marks (`…` -> `...`, `«`/`»`/`“`/`”`/`″`/`„` -> `"`). <!-- `’`/`‘`/`‛`/`ʿ` -> `'`,  `ᵉ`/`ᵉʳ` -> `e`/`er`, `‚` -> `,` -->

<!-- Those details are described in the paper:
[_«&nbsp;The Claire French Dialogue Dataset&nbsp;»_](https://arxiv.org/abs/2311.16840) (2023).-->


## License

Given that some of the corpora used for training are only available under CC-BY-NC-SA licenses,
Claire-Dialogue-English-0.1 is made available under the [CC-BY-NC-SA 4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/).


## Citations

When using the CEDD corpus, please cite this page:

<!-- ✍ Julie Hunter, Jérôme Louradour, Virgile Rennard, Ismaïl Harrando, Guokan Shang, Jean-Pierre Lorré  (2023)
[The Claire French Dialogue Dataset](https://arxiv.org/abs/2311.16840) -->

```bibtex
@misc{openllm2024claire_en,
  author = {Julie Hunter and Jérôme Louradour and Virgile Rennard and Ismaïl Harrando and Guokan Shang and Jean-Pierre Lorré},
  title = {The Claire English Dialogue Dataset},
  year = {2024},
  publisher = {HuggingFace},
  journal = {HuggingFace},
  howpublished = {\url{https://huggingface.co/datasets/OpenLLM-France/Claire-Dialogue-English-0.1}},
}
```

You should also provide citations for all of the original corpora. They are listed below.

* **Accueil UBS**
  * Pascale Nicolas, Sabine Letellier-Zarshenas, Igor Schadle, Jean-Yves Antoine, Jean Caelen (2002). [Towards a large corpus of spoken dialogue in French that will be freely available: the "Parole Publique" project and its first realisations](https://www.info.univ-tours.fr/~antoine/parole_publique/articles/2002_LREC_CORP.pdf). _Third European Conference on Language Resources and Evaluation_ (LREC). Las Palmas de Gran Canaria, Espagne.
  * Jean-Yves Antoine, Jerome Goulian, Jeanne Villaneau, Marc le Tallec (2009). [Word Order Phenomena in Spoken French : a Study on Four Corpora of Task-Oriented Dialogue and its Consequences on Language Processing](https://www.info.univ-tours.fr/~antoine/articles/2009_Corpus_Linguistics.pdf). _Corpus Linguistics_, Liverpool, UK.
* **ACSYNT**
  * Cognition, Langue, Langages, Ergonomie - UMR 5263 (CLLE) (2013). [ACSYNT [Corpus]](https://hdl.handle.net/11403/sldr000832/v1). [ORTOLANG](www.ortolang.fr) (Open Resources and TOols for LANGuage).
* **CFPP**
  * Branca-Rosoff S., Fleury S., Lefeuvre F., Pires M., 2012, [Discours sur la ville. Présentation du Corpus de Français Parlé Parisien des années 2000](http://cfpp2000.univ-paris3.fr/CFPP2000.pdf) (CFPP2000). 
  * CLESTHIA - Langage, systèmes, discours - EA 7345 (CLESTHIA) (2018). [CFPP2000 [Corpus]](https://hdl.handle.net/11403/cfpp2000/v1). [ORTOLANG](www.ortolang.fr) (Open Resources and TOols for LANGuage), v1.
* **CID**
  * Roxane Bertrand, Philippe Blache, Robert Espesser, Gaëlle Ferré, Christine Meunier, Béatrice Priego-Valverde, Stéphane Rauzy (2008). [Le CID — Corpus of Interactional Data — Annotation et Exploitation Multimodale de Parole Conversationnelle](https://hal.science/hal-00349893). _Traitement Automatique des Langues_, vol. 49, no. 3.
  * Philippe Blache, Roxane Bertrand, Brigitte Bigi et al. (2010). [Multimodal annotation of conversational data](http://portal.acm.org/citation.cfm?id=1868749). _Proceedings of the Fourth Linguistic Annotation Workshop_. 
  * Laboratoire parole et langage - UMR 7309 (LPL) (2021). [Transcriptions du corpus CID [Corpus]](https://hdl.handle.net/11403/sldr000720/v1). [ORTOLANG](www.ortolang.fr) (Open Resources and TOols for LANGuage).
* **CLAPI**
  * CLAPI, [http://clapi.icar.cnrs.fr](http://clapi.icar.cnrs.fr)
  * Groupe ICOR (H. Baldauf-Quilliatre, I. Colon de Carvajal, C. Etienne, E. Jouin-Chardon, S. Teston-Bonnard, V. Traverso) (2016). [CLAPI, une base de données multimodale pour la parole en interaction : apports et dilemmes](https://shs.hal.science/halshs-01316283/). In Avanzi M., Béguelin M.-J. & Diémoz F. (eds), _Corpus de français parlés et français parlés des corpus, Corpus_ 15.
* **ESLO**
  * Iris Eshkol-Taravella, Olivier Baude, Denis Maurel, Linda Hriba, Céline Dugua, Isabelle Tellier (2012). Un grand corpus oral « disponible » : le corpus d’Orléans 1968-2012, _Ressources linguistiques libres, TAL_. Volume 52 – n° 3/2011, 17-46.
  * Laboratoire Ligérien de Linguistique - UMR 7270 (LLL) (2023). [ESLO [Corpus]](https://hdl.handle.net/11403/eslo/v1). [ORTOLANG](www.ortolang.fr) (Open Resources and TOols for LANGuage), v1.
* **FREDSum**
  * Virgile Rennard, Guokan Shang, Damien Grari, Julie Hunter, Michalis Vazirgiannis (forthcoming). FREDSum: A Dialogue Summarization Corpus for French Political Debates. _Findings of Empirical Methods in Natural Language Processsing_ (EMNLP).
* **LinTO**
  * Lila Gravellier, Julie Hunter, Philippe Muller, Thomas Pellegrini, Isabelle Ferrané (2021).
[Weakly Supervised Discourse Segmentation for Multiparty Oral Conversation](https://aclanthology.org/2021.emnlp-main.104/).
_The 2021 Conference on Empirical Methods in Natural Language Processing_ (EMNLP), pp. 1381–1392.
* **OFROM**
  * Mathieu Avanzi, Marie-José Béguelin, Gilles Corminboeuf, Federica Diémoz, Laure Anne Johnsen (2012-2023). [Corpus OFROM – Corpus oral de français de Suisse romande](ofrom.unine.ch). Université de Neuchâtel.
  * Mathieu Avanzi, Marie-José Béguelin, Federica Diémoz (2016). [Présentation du corpus OFROM – Corpus oral de français de Suisse romande](ofrom.unine.ch/uploads/Documents/AM-MJB-FD_GC_LAJ_OFROM_23.pdf). Université de Neuchâtel.
  * Mathieu Avanzi, Marie-José Béguelin, Federica Diémoz (2016). De l’archive de parole au corpus de référence. Le corpus oral de français de Suisse romande (OFROM). _Actes du colloque Corpus de Français Parlés et Français Parlés des Corpus_ (= Corpus 15), 309-342.
  * Gilles Corminboeuf, Julie Rothenbühler, Maguelone Sauzet (éds) (2020). [Français parlés et français ‘tout court’](studialinguisticaromanica.org/index.php/slr/issue/view/4). _Studia Linguistica Romanica_ n°4, publication électronique.
* **ORFEO** (pour chaque corpus issu du projet ORFEO)
  * Jeanne-Marie Debaisieux, Christophe Benzitoun, Henri-José Deulofeu. Le projet ORFÉO : un corpus d’étude pour le français contemporain, _Corpus 15_, Actes du colloque Corpus de Français Parlés et Français Parlés des Corpus.
  * Carruthers, Janice (2008). Annotating an Oral Corpus using the Text Encoding Initiative. Methodology, Problems, Solutions, _Journal of French Language Studies_ 18(1), 103-119.
  * Agnès Tutin, Francis Grossmann (2014). _L’écrit scientifique : du lexique au discours. Autour de Scientext_. Presses de l’Université de Rennes.
* **ORFEO/CFPB**
  * Anne Dister, Emmanuelle Labeau (2017). [Le corpus de français parlé à Bruxelles: origines, hypothèses, développements et prédictions](https://www.semanticscholar.org/paper/Le-corpus-de-fran%C3%A7ais-parl%C3%A9-%C3%A0-Bruxelles%3A-origines%2C-Dister-Labeau/0fe858f6b8c1ce49a2e43b34494c2e76922162fa).
* **ORFEO/C-Oral-Rom**
  * Cresti Emanuela, Bacelar do Nascimento Fernanda, Moreno Sandoval Antonio, Veronis Jean, Martin Philippe, Kalid Choukri (2005).  The C-ORAL-ROM CORPUS: A Multilingual Resource of Spontaneous Speech for Romance Languages. _Studies in Corpus Linguistics_, 15. John Benjamins Publishing Company 304 pp. (incl. DVD).
* **ORFEO/CRFP**
  * Équipe Delic (2004). Recherches sur le français parlé n° 18, « Autour du Corpus de référence du français parlé »  Publications de l’université de Provence, 265 p.
* **ORFEO/Valibel**
  * Anne Dister, Michel Francard, Philippe Hambye, Anne-Catherine Simon (2009). [Du corpus à la banque de données. Du son, des textes et des métadonnées. L'évolution de banque de données textuelles orales VALIBEL (1989-2009)](https://cdn.uclouvain.be/public/Exports%20reddot/valibel/documents/Dister_et_al_2009_Cahiers.pdf), _Cahiers de Linguistique_ 33/2, 113-129.
* **OTG**
  * Pascale Nicolas, Sabine Letellier-Zarshenas, Igor Schadle, Jean-Yves Antoine, Jean Caelen (2002). [Towards a large corpus of spoken dialogue in French that will be freely available: the "Parole Publique" project and its first realisations](https://www.info.univ-tours.fr/~antoine/parole_publique/articles/2002_LREC_CORP.pdf). _Third European Conference on Language Resources and Evaluation_ (LREC). Las Palmas de Gran Canaria, Espagne.
  * Jean-Yves Antoine, Sabine Letellier-Zarshenas, Pascale Nicolas, Igor Schadle (2002). [Corpus OTG et ECOLE_MASSY : vers la constitution d’un collection de corpus francophones de dialogue oral diffusés librement](https://www.info.univ-tours.fr/~antoine/parole_publique/articles/2002_TALN_CORP.pdf). _Actes TALN_ 2002. Nancy, France.
* **Paris Stories**
  * Sylvain Kahane, Bernard Caron, Emmett Strickland, Kim Gerdes. Annotation guidelines of UD and SUD treebanks for spoken corpora: A proposal. _Proceedings of the 20th International Workshop on Treebanks and Linguistic Theories_ (TLT, SyntaxFest 2021).
* **PFC**
  * Jacques Durand, Bernard Laks, Chantal Lyche (2009). Le projet PFC: une source de données primaires structurées. In J. Durand, B. Laks et C. Lyche (eds)(2009) _Phonologie, variation et accents du français_. Paris: Hermès. pp. 19-61.
  * Modèles, Dynamiques, Corpus - UMR 7114 (MoDyCo), Université de Groningen (RUG) (2017). [PFC - Phonologie du Français Contemporain [Corpus]](https://hdl.handle.net/11403/pfc/v1). [ORTOLANG](www.ortolang.fr) (Open Resources and TOols for LANGuage), v1.
* **Rhapsodie**
  * see [https://rhapsodie.modyco.fr/propriete-intellectuelle/](https://rhapsodie.modyco.fr/propriete-intellectuelle/)
* **SUMM-RE**
  * Hiroyoshi Yamasaki, Jérôme Louradour, Julie Hunter, Laurent Prévot (forthcoming). Transcribing And Aligning Conversational Speech: A Hybrid Pipeline Applied To French Conversations. _Workshop on Automatic Speech Recognition and Understanding_ (ASRU).
* **TCOF**
  * Analyse et Traitement Informatique de la Langue Française (2020). [TCOF : Traitement de Corpus Oraux en Français [Corpus]](https://www.ortolang.fr/market/corpora/tcof/v2.1). _ORTOLANG (Open Resources and TOols for LANGuage)_ 
* **Theatre Classique**
  * French Drama Corpus (FreDraCor): A TEI P5 Version of Paul Fièvre's "Théâtre Classique" Corpus. Edited by Carsten Milling, Frank Fischer and Mathias Göbel. Hosted on GitHub, 2021 – [https://github.com/dracor-org/fredracor](https://github.com/dracor-org/fredracor)


## Contact

contact@openllm-france.fr