Search Results for author: Yen-chen Wu

Found 9 papers, 2 papers with code

Clipping Loops for Sample-Efficient Dialogue Policy Optimisation

no code implementations NAACL 2021 Yen-chen Wu, Carl Edward Rasmussen

Second, in advantage clipping, we estimate and clip the advantages of useless responses and normal ones separately.

Tree-Structured Semantic Encoder with Knowledge Sharing for Domain Adaptation in Natural Language Generation

no code implementations WS 2019 Bo-Hsiang Tseng, Paweł Budzianowski, Yen-chen Wu, Milica Gašić

Domain adaptation in natural language generation (NLG) remains challenging because of the high complexity of input semantics across domains and limited data of a target domain.

Decoder Domain Adaptation +2

Addressing Objects and Their Relations: The Conversational Entity Dialogue Model

no code implementations WS 2018 Stefan Ultes, Paweł\ Budzianowski, Iñigo Casanueva, Lina Rojas-Barahona, Bo-Hsiang Tseng, Yen-chen Wu, Steve Young, Milica Gašić

Statistical spoken dialogue systems usually rely on a single- or multi-domain dialogue model that is restricted in its capabilities of modelling complex dialogue structures, e. g., relations.

Spoken Dialogue Systems

Interactive Spoken Content Retrieval by Deep Reinforcement Learning

no code implementations16 Sep 2016 Yen-chen Wu, Tzu-Hsiang Lin, Yang-De Chen, Hung-Yi Lee, Lin-shan Lee

In our previous work, some hand-crafted states estimated from the present retrieval results are used to determine the proper actions.

Deep Reinforcement Learning Q-Learning +5

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