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The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
In: Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021) ; https://hal.archives-ouvertes.fr/hal-03466171 ; Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021), Aug 2021, Online, France. pp.96-120, ⟨10.18653/v1/2021.gem-1.10⟩ (2021)
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2
THEaiTRobot 1.0
Rosa, Rudolf; Dušek, Ondřej; Kocmi, Tom. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2021. : The Švanda Theatre in Smíchov, 2021. : The Academy of Performing Arts in Prague, Theatre Faculty (DAMU), 2021
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3
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics ...
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MiRANews: Dataset and Benchmarks for Multi-Resource-Assisted News Summarization ...
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AggGen: Ordering and Aggregating while Generating ...
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Discovering Dialogue Slots with Weak Supervision ...
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7
One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech ...
Abstract: We introduce an approach to multilingual speech synthesis which uses the meta-learning concept of contextual parameter generation and produces natural-sounding multilingual speech using more languages and less training data than previous approaches. Our model is based on Tacotron 2 with a fully convolutional input text encoder whose weights are predicted by a separate parameter generator network. To boost voice cloning, the model uses an adversarial speaker classifier with a gradient reversal layer that removes speaker-specific information from the encoder. We arranged two experiments to compare our model with baselines using various levels of cross-lingual parameter sharing, in order to evaluate: (1) stability and performance when training on low amounts of data, (2) pronunciation accuracy and voice quality of code-switching synthesis. For training, we used the CSS10 dataset and our new small dataset based on Common Voice recordings in five languages. Our model is shown to effectively share information ... : Accepted to INTERSPEECH 2020; for the source files, see https://github.com/Tomiinek/Multilingual_Text_to_Speech ...
Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Machine Learning cs.LG
URL: https://arxiv.org/abs/2008.00768
https://dx.doi.org/10.48550/arxiv.2008.00768
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8
Neural Generation for Czech: Data and Baselines ...
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Evaluating the State-of-the-Art of End-to-End Natural Language Generation: The E2E NLG Challenge ...
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RankME: Reliable Human Ratings for Natural Language Generation ...
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11
Better Conversations by Modeling,Filtering,and Optimizing for Coherence and Diversity ...
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12
Findings of the E2E NLG Challenge ...
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13
Czech restaurant information dataset for NLG
Dušek, Ondřej; Jurčíček, Filip; Dvořák, Josef. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2017
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14
Khresmoi Summary Translation Test Data 2.0
Dušek, Ondřej; Hajič, Jan; Hlaváčová, Jaroslava. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2017
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15
Khresmoi Query Translation Test Data 2.0
Pecina, Pavel; Dušek, Ondřej; Hajič, Jan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2017
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The E2E Dataset: New Challenges For End-to-End Generation ...
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The E2E Challenge Dataset ...
Novikova, Jekaterina; Dusek, Ondrej; Rieser, Verena. - : Heriot-Watt University, 2017
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CzEng 1.6: Enlarged Czech-English Parallel Corpus with Processing Tools Dockered
Bojar, Ondřej [Verfasser]; Dušek, Ondřej [Verfasser]; Kocmi, Tom [Verfasser]. - Aachen : Universitätsbibliothek der RWTH Aachen, 2016
DNB Subject Category Language
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19
Alex Context NLG Dataset
Dušek, Ondřej; Jurčíček, Filip. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2016
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20
Vystadial 2016 – Czech data
Plátek, Ondřej; Dušek, Ondřej; Jurčíček, Filip. - : Charles University, Faculty of Mathematics and Physics, 2016
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