Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
text
Languages:
English
Size:
100K - 1M
ArXiv:
Tags:
conversational
text-generation
conditional-text-generation
dialogue-modeling
dialogue-generation
License:
Update README.md
Browse files
README.md
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@@ -83,7 +83,7 @@ For more information, you can look at the following documents:
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<td><a href="https://www.statmt.org/europarl/">Europarl</a></td>
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<td>The Europarl parallel corpus</td>
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<td>56M</td>
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<td>11K</td>
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<td>No copyright restrictions. If you use this data in your research, please contact phi@jhu.edu</td>
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</tr>
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<td><a href="https://anc.org/data/oanc/contents/#charlotte">Charlotte Narratives</a></td>
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<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>
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<td>200K</td>
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<td>93</td>
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<td><a href="
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<td><a href="https://anc.org/data/oanc/contents/#switchboard">Switchboard</a></td>
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<td>The corpus consists of approximately 260 hours of speech and was originally collected by Texas Instruments in 1990-1, under DARPA sponsorship.</td>
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<td>3M</td>
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<td>2320</td>
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<td><a href="https://catalog.ldc.upenn.edu/LDC97S62">LDC User
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<td><a href="https://huggingface.co/datasets/ccdv/mediasum">MediaSum</a></td>
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<td>MediaSum dataset for summarization</td>
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<td>720M</td>
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<td>458K</td>
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<td><a href="https://github.com/zcgzcgzcg1/MediaSum">For research purposes only</a></td>
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<td><a href="https://groups.inf.ed.ac.uk/ami/corpus/">AMI</a></td>
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<td>The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings.</td>
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<td>712K</td>
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<td><a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></td>
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<td><a href="https://groups.inf.ed.ac.uk/ami/icsi/">ICSI</a></td>
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<td>About 70 hours of meeting recordings.</td>
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<td>804K</td>
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<td><1K</td>
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<td><a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></td>
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<td><a href="https://redialdata.github.io/website/">ReDial</a></td>
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<td>ReDial (Recommendation Dialogues) is an annotated dataset of dialogues, where users recommend movies to each other.</td>
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<td>1.
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<td><a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></td>
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</tr>
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<td><a href="https://github.com/facebookresearch/opendialkg">OpenDialKG</a></td>
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<td>OpenDialKG is a dataset of conversations between two crowdsourcing agents engaging in a dialog about a given topic.</td>
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<td>1M</td>
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<td><a href="https://creativecommons.org/licenses/by-nc/4.0/legalcode">CC-BY-NC-4.0</a></td>
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<td><a href="https://github.com/asappresearch/abcd">ABCD</a></td>
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<td>Action-Based Conversations Dataset.</td>
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<td>1.5M</td>
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<td><a href="https://github.com/asappresearch/abcd/blob/master/LICENSE">MIT</a></td>
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<td><a href="https://github.com/google/airdialogue">AirDialogue</a></td>
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<td>AirDialogue is a benchmark dataset for goal-oriented dialogue generation research.</td>
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<td>37M</td>
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<td><a href="https://github.com/google/airdialogue/blob/master/LICENSE">Apache License 2.0</a></td>
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<td><a href="https://huggingface.co/datasets/pfb30/multi_woz_v22">MULTIWOZ2_2</a></td>
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<td>Multi-Domain Wizard-of-Oz dataset (MultiWOZ), a fully-labeled collection of human-human written conversations spanning over multiple domains and topics.</td>
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<td>1.9M</td>
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<td><a href="https://choosealicense.com/licenses/apache-2.0/">Apache License 2.0</a></td>
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</tr>
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<tr>
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<td><a href="https://github.com/awslabs/multi-domain-goal-oriented-dialogues-dataset">MulDoGO</a></td>
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<td>Conversations from the airline, fastfood, finance, insurance, media, and software domains.</td>
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<td>10M</td>
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<td><a href="https://github.com/awslabs/multi-domain-goal-oriented-dialogues-dataset/blob/master/LICENSE.txt">CDLA Permissive License</a></td>
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<td><a href="https://huggingface.co/datasets/li2017dailydialog/daily_dialog">DailyDialog</a></td>
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<td>High-quality multi-turn dialog dataset.</td>
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<td>1.2M</td>
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<td>13K</td>
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<td><a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a></td>
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</tr>
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<td><a href="">British National Corpus (BNC)</a></td>
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<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>
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<td>110M</td>
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<td><a href="http://www.natcorp.ox.ac.uk/docs/licence.html">BCN License</a></td>
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You should also provide citations for all of the original corpora. They are listed below.
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* **ORFEO/C-Oral-Rom**
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* 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).
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* **ORFEO/CRFP**
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* 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.
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* **ORFEO/Valibel**
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* 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.
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* **OTG**
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* 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.
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* 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.
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* **Paris Stories**
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* 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).
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* **PFC**
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* 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.
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* 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.
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* **Rhapsodie**
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* see [https://rhapsodie.modyco.fr/propriete-intellectuelle/](https://rhapsodie.modyco.fr/propriete-intellectuelle/)
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* **SUMM-RE**
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* 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).
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* **TCOF**
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* 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)_
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* **Theatre Classique**
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* 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)
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## Contact
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<td><a href="https://www.statmt.org/europarl/">Europarl</a></td>
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<td>The Europarl parallel corpus</td>
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<td>56M</td>
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<td>214K</td>
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<td>11K</td>
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<td>No copyright restrictions. If you use this data in your research, please contact phi@jhu.edu</td>
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</tr>
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<td><a href="https://anc.org/data/oanc/contents/#charlotte">Charlotte Narratives</a></td>
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<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>
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<td>200K</td>
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<td>2.7K</td>
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<td>93</td>
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<td><a href="https://anc.org/data/oanc/download/">Available for download and use for research and development, including commercial development.</a></td>
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</tr>
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<tr>
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<td><a href="https://anc.org/data/oanc/contents/#switchboard">Switchboard</a></td>
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<td>The corpus consists of approximately 260 hours of speech and was originally collected by Texas Instruments in 1990-1, under DARPA sponsorship.</td>
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<td>3M</td>
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<td>290K</td>
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<td>2320</td>
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<td><a href="https://catalog.ldc.upenn.edu/LDC97S62">LDC User Ageement for Non-Members.</a></td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/ccdv/mediasum">MediaSum</a></td>
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<td>MediaSum dataset for summarization</td>
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<td>720M</td>
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<td>13M</td>
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<td>458K</td>
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<td><a href="https://github.com/zcgzcgzcg1/MediaSum">For research purposes only</a></td>
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</tr>
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<td><a href="https://groups.inf.ed.ac.uk/ami/corpus/">AMI</a></td>
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<td>The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings.</td>
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<td>712K</td>
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<td>75K</td>
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<td>139</td>
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<td><a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></td>
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</tr>
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<tr>
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<td><a href="https://groups.inf.ed.ac.uk/ami/icsi/">ICSI</a></td>
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<td>About 70 hours of meeting recordings.</td>
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<td>804K</td>
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<td>64K</td>
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<td><1K</td>
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<td><a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></td>
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</tr>
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<tr>
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<td><a href="https://redialdata.github.io/website/">ReDial</a></td>
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<td>ReDial (Recommendation Dialogues) is an annotated dataset of dialogues, where users recommend movies to each other.</td>
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<td>1.5M</td>
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<td>139K</td>
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<td>11K</td>
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<td><a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></td>
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</tr>
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<tr>
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<td><a href="https://github.com/facebookresearch/opendialkg">OpenDialKG</a></td>
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<td>OpenDialKG is a dataset of conversations between two crowdsourcing agents engaging in a dialog about a given topic.</td>
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<td>1M</td>
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<td>12K</td>
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<td><a href="https://creativecommons.org/licenses/by-nc/4.0/legalcode">CC-BY-NC-4.0</a></td>
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</tr>
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<tr>
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<td><a href="https://github.com/asappresearch/abcd">ABCD</a></td>
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<td>Action-Based Conversations Dataset.</td>
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<td>1.5M</td>
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<td>10K</td>
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<td><a href="https://github.com/asappresearch/abcd/blob/master/LICENSE">MIT</a></td>
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</tr>
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<tr>
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<td><a href="https://github.com/google/airdialogue">AirDialogue</a></td>
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<td>AirDialogue is a benchmark dataset for goal-oriented dialogue generation research.</td>
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<td>37M</td>
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<td>4.6M</td>
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<td>361K</td>
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<td><a href="https://github.com/google/airdialogue/blob/master/LICENSE">Apache License 2.0</a></td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/pfb30/multi_woz_v22">MULTIWOZ2_2</a></td>
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<td>Multi-Domain Wizard-of-Oz dataset (MultiWOZ), a fully-labeled collection of human-human written conversations spanning over multiple domains and topics.</td>
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<td>1.9M</td>
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<td>143K</td>
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<td>10.4K</td>
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<td><a href="https://choosealicense.com/licenses/apache-2.0/">Apache License 2.0</a></td>
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</tr>
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<tr>
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<td><a href="https://github.com/awslabs/multi-domain-goal-oriented-dialogues-dataset">MulDoGO</a></td>
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<td>Conversations from the airline, fastfood, finance, insurance, media, and software domains.</td>
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<td>10M</td>
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<td>892K</td>
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<td>63K</td>
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<td><a href="https://github.com/awslabs/multi-domain-goal-oriented-dialogues-dataset/blob/master/LICENSE.txt">CDLA Permissive License</a></td>
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</tr>
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<td><a href="https://huggingface.co/datasets/li2017dailydialog/daily_dialog">DailyDialog</a></td>
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<td>High-quality multi-turn dialog dataset.</td>
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<td>1.2M</td>
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<td>102K</td>102K</td>
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<td>13K</td>
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<td><a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a></td>
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</tr>
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<td><a href="">British National Corpus (BNC)</a></td>
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<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>
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<td>110M</td>
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<td>663K</td>
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<td>0.9K</td>
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<td><a href="http://www.natcorp.ox.ac.uk/docs/licence.html">BCN License</a></td>
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</tr>
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You should also provide citations for all of the original corpora. They are listed below.
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* **Europarl**
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* Philipp Koehn (2005). [Europarl: A Parallel Corpus for Statistical Machine Translation](https://aclanthology.org/2005.mtsummit-papers.11/). _Proceedings of Machine Translation Summit X: Papers_, Phuket, Thailand.
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* **Charlotte Narratives**
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* [OANC link](https://anc.org/data/oanc/contents/#charlotte).
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* **Switchboard**
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* John J. Godfrey, Edward Holliman (1993). [Switchboard-1 Release 2](https://catalog.ldc.upenn.edu/LDC97S62), Linguistic Data Consortium (LDC), Philadelphia.
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* **MediaSum**
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* Zhu, Chenguang and Liu, Yang and Mei, Jie and Zeng, Michael (2021). [MediaSum: A Large-scale Media Interview Dataset for Dialogue Summarization](https://aclanthology.org/2021.naacl-main.474/). _arXiv preprint arXiv:2103.06410_.
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* **AMI**
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* I. McCowan, J. Carletta, W. Kraaij, S. Ashby, S. Bourban, M. Flynn, M. Guillemot, T. Hain, J. Kadlec, V. Karaiskos, M.Kronenthal, G. Lathoud, M. Lincoln, A. Lisowska, W. Post, D. Reidsma, and P. Wellne (2005). [The AMI meeting corpus: a pre-announcement](https://dl.acm.org/doi/10.1007/11677482_3), _Machine Learning for Multimodal Interaction_, Edinburgh, UK.
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* **ICSI**
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* Virgile Rennard, Guokan Shang, Julie Hunter, Michalis Vazirgiannis (2023). [Abstractive Meeting Summarization: A Survey](https://arxiv.org/abs/2208.04163). _TACL_, Cambridge, MA.
|
319 |
+
* **ReDial**
|
320 |
+
* Li, Raymond and Kahou, Samira Ebrahimi and Schulz, Hannes and Michalski, Vincent and Charlin, Laurent and Pal, Chris (2018). [Towards Deep Conversational Recommendations](https://link). _NeurIPS 2018_, Montreal.
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321 |
+
* **OpenDialKG**
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322 |
+
* Seungwhan Moon, Pararth Shah, Anuj Kumar, Rajen Subba (2019). [OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs](https://aclanthology.org/P19-1081/). _ACL_, Florence, Italy.
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323 |
+
* **ABCD**
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324 |
+
* Derek Chen, Howard Chen, Yi Yang, Alexander Lin, Zhou Yu (2021). [Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task-Oriented Dialogue Systems](https://aclanthology.org/2021.naacl-main.239/). _NAACL_, Online.
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325 |
+
* **AirDialogue**
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326 |
+
* Wei Wei, Quoc Le, Andrew Dai, Jia Li (2018). [paper title](https://aclanthology.org/D18-1419/). _EMNLP_, Brussels, Belgium.
|
327 |
+
* **MULTIWOZ2_2**
|
328 |
+
* Eric, Mihail and Goel, Rahul and Paul, Shachi and Sethi, Abhishek and Agarwal, Sanchit and Gao, Shuyag and Hakkani-Tur, Dilek (2019). [MultiWOZ 2.1: Multi-Domain Dialogue State Corrections and State Tracking Baselines](https://arxiv.org/abs/2007.12720). _arxiv_.
|
329 |
+
* **MultiDoGO**
|
330 |
+
* Denis Peskov, Nancy Clarke, Jason Krone, Brigi Fodor, Yi Zhang, Adel Youssef, Mona Diab (2019). [Multi-Domain Goal-Oriented Dialogues (MultiDoGO): Strategies toward Curating and Annotating Large Scale Dialogue Data](https://www.aclweb.org/anthology/D19-1460). _EMNLP_, Hong Kong, China.
|
331 |
+
* **Chit-Chat**
|
332 |
+
* Myers, Will and Etchart, Tyler and Fulda, Nancy (2020). [Conversational Scaffolding: An Analogy-based Approach to Response Prioritization in Open-domain Dialogs](https://www.scitepress.org/Papers/2020/89399/89399.pdf).
|
333 |
+
* **DailyDialog**
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334 |
+
* Yanran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, Shuzi Niu (2017). [DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset](https://aclanthology.org/I17-1099/). _IJCNLP_, Taipei, Taiwan.
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335 |
+
* **British National Corpus (BNC)**
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336 |
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* [The British National Corpus online](http://www.natcorp.ox.ac.uk/).
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337 |
+
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338 |
+
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339 |
+
Some of the listed datasets were collected from the DialogStudio compilation, which is also to be cited:
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340 |
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* **DialogStudio**
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341 |
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* Zhang, Jianguo and Qian, Kun and Liu, Zhiwei and Heinecke, Shelby and Meng, Rui and Liu, Ye and Yu, Zhou and Savarese, Silvio and Xiong, Caiming (2023). [DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI](https://arxiv.org/abs/2307.10172). _arXiv preprint arXiv:2307.10172_.
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## Contact
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