Search Results for author: Tomáš Nekvinda

Found 3 papers, 3 papers with code

Shades of BLEU, Flavours of Success: The Case of MultiWOZ

1 code implementation ACL (GEM) 2021 Tomáš Nekvinda, Ondřej Dušek

The MultiWOZ dataset (Budzianowski et al., 2018) is frequently used for benchmarking context-to-response abilities of task-oriented dialogue systems.

Task-Oriented Dialogue Systems

AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue with Pre-Trained Language Models

1 code implementation EMNLP (NLP4ConvAI) 2021 Jonáš Kulhánek, Vojtěch Hudeček, Tomáš Nekvinda, Ondřej Dušek

Our model substantially outperforms the baseline on the MultiWOZ data and shows competitive performance with state of the art in both automatic and human evaluation.

Ranked #3 on End-To-End Dialogue Modelling on MULTIWOZ 2.0 (using extra training data)

End-To-End Dialogue Modelling Translation

One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech

1 code implementation3 Aug 2020 Tomáš Nekvinda, Ondřej Dušek

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.

Meta-Learning Speech Synthesis

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