Additional three Czech reference translations of the whole WMT 2011 data set (http://www.statmt.org/wmt11/test.tgz), translated from the German originals. Original segmentation of the WMT 2011 data is preserved. and This project has been sponsored by the grants GAČR P406/11/1499 and EuroMatrixPlus (FP7-ICT-2007-3-231720 of the EU and 7E09003+7E11051 of the Ministry of Education, Youth and Sports of the Czech Republic)
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.
This is a dataset for natural language generation (NLG) in task-oriented spoken dialogue systems with Czech as the target language. It originated as a translation of the English San Francisco Restaurants dataset by Wen et al. (2015).
It includes input dialogue acts and the corresponding output natural language paraphrases in Czech. Since the dataset is intended for recurrent neural network based NLG systems using delexicalization, inflection tables for all slot values appearing verbatim in the text are provided.
CzEng 1.0 is the fourth release of a sentence-parallel Czech-English corpus compiled at the Institute of Formal and Applied Linguistics (ÚFAL) freely available for non-commercial research purposes.
CzEng 1.0 contains 15 million parallel sentences (233 million English and 206 million Czech tokens) from seven different types of sources automatically annotated at surface and deep (a- and t-) layers of syntactic representation. and EuroMatrix Plus (FP7-ICT-2007-3-231720 of the EU and 7E09003+7E11051 of the Ministry of Education, Youth and Sports of the Czech Republic),
Faust (FP7-ICT-2009-4-247762 of the EU and 7E11041 of the Ministry of Education, Youth and Sports of the Czech Republic),
GAČR P406/10/P259,
GAUK 116310,
GAUK 4226/2011
This package contains data sets for development and testing of machine translation of medical search short queries between Czech, English, French, and German. The queries come from general public and medical experts. and This work was supported by the EU FP7 project Khresmoi (European Comission contract No. 257528). The language resources are distributed by the LINDAT/Clarin project of the Ministry of Education, Youth and Sports of the Czech Republic (project no. LM2010013).
We thank Health on the Net Foundation for granting the license for the English general public queries, TRIP database for granting the license for the English medical expert queries, and three anonymous translators and three medical experts for translating amd revising the data.
This package contains data sets for development and testing of machine translation of medical queries between Czech, English, French, German, Hungarian, Polish, Spanish ans Swedish. The queries come from general public and medical experts. This is version 2.0 extending the previous version by adding Hungarian, Polish, Spanish, and Swedish translations.
This package contains data sets for development and testing of machine translation of sentences from summaries of medical articles between Czech, English, French, and German. and This work was supported by the EU FP7 project Khresmoi (European Comission contract No. 257528). The language resources are distributed by the LINDAT/Clarin project of the Ministry of Education, Youth and Sports of the Czech Republic (project no. LM2010013). We thank all the data providers and copyright holders for providing the source data and anonymous experts for translating the sentences.
This package contains data sets for development (Section dev) and testing (Section test) of machine translation of sentences from summaries of medical articles between Czech, English, French, German, Hungarian, Polish, Spanish
and Swedish. Version 2.0 extends the previous version by adding Hungarian, Polish, Spanish, and Swedish translations.
MTMonkey is a web service which handles and distributes JSON-encoded HTTP requests for machine translation (MT) among multiple machines running an MT system, including text pre- and post processing.
It consists of an application server and remote workers which handle text processing and communicate translation requests to MT systems. The communication between the application server and the workers is based on the XML-RPC protocol. and The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 257528 (KHRESMOI). This work has been using language resources developed and/or stored and/or distributed by the LINDAT-Clarin project of the Ministry of Education of the Czech Republic (project LM2010013). This work has been supported by the AMALACH grant (DF12P01OVV02) of the Ministry of Culture of the Czech Republic.
The THEaiTRobot 1.0 tool allows the user to interactively generate scripts for individual theatre play scenes.
The tool is based on GPT-2 XL generative language model, using the model without any fine-tuning, as we found that with a prompt formatted as a part of a theatre play script, the model usually generates continuation that retains the format.
We encountered numerous problems when generating the script in this way. We managed to tackle some of the problems with various adjustments, but some of them remain to be solved in a future version.
THEaiTRobot 1.0 was used to generate the first THEaiTRE play, "AI: Když robot píše hru" ("AI: When a robot writes a play").