Alex Context NLG Dataset

  Authors

Dušek, Ondřej and Jurčíček, Filip

  Item identifier

http://hdl.handle.net/11234/1-1675

 Project URL

https://github.com/UFAL-DSG/alex_context_nlg_dataset

 Date issued

2016-04-05

 Type

corpus, text

 Size

1859 entries, 5577 sentences

 Language(s)

English

 Description

A dataset intended for fully trainable natural language generation (NLG) systems in task-oriented spoken dialogue systems (SDS), covering the English public transport information domain. It includes preceding context (user utterance) along with each data instance (pair of source meaning representation and target natural language paraphrase to be generated). Taking the form of the previous user utterance into account for generating the system response allows NLG systems trained on this dataset to entrain (adapt) to the preceding utterance, i.e., reuse wording and syntactic structure. This should presumably improve the perceived naturalness of the output, and may even lead to a higher task success rate. Crowdsourcing has been used to obtain natural context user utterances as well as natural system responses to be generated.

 Publisher

Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)

 Acknowledgement

Grantová agentura Univerzity Karlovy v Praze

Project code: GAUK 2058214

Project name: Adaptivní generátor přirozeného jazyka

 

Ministerstvo školství, mládeže a tělovýchovy České republiky

Project code: LK11221

Project name: Vývoj metod pro návrh statistických mluvených dialogových systémů

 

Univerzita Karlova v Praze (mimo GAUK)

Project code: SVV 260 333

Project name: Specifický vysokoškolský výzkum

 Subject(s)

dialogue system natural language generation dialogue alignment entrainment

 Collection(s)

LINDAT / CLARIAH-CZ Data & Tools

Show full item record