activity
20182021
most citedTransferable Dialogue Systems and User Simulators

2 citations · 3 across the 7 of their papers we have counts for

collaborators

11 papers

cs.CL20212 cited

Transferable Dialogue Systems and User Simulators

Bo-Hsiang Tseng, Yinpei Dai, Florian Kreyssig +1

One of the difficulties in training dialogue systems is the lack of training data. We explore the possibility of creating dialogue data through the interaction between a dialogue s…

cs.AI2021

CREAD: Combined Resolution of Ellipses and Anaphora in Dialogues

Bo-Hsiang Tseng, Shruti Bhargava, Jiarui Lu +4

Anaphora and ellipses are two common phenomena in dialogues. Without resolving referring expressions and information omission, dialogue systems may fail to generate consistent and…

cs.CL2020

A Generative Model for Joint Natural Language Understanding and Generation

Bo-Hsiang Tseng, Jianpeng Cheng, Yimai Fang +1

Natural language understanding (NLU) and natural language generation (NLG) are two fundamental and related tasks in building task-oriented dialogue systems with opposite objectives…

cs.CL2019

Semi-supervised Bootstrapping of Dialogue State Trackers for Task Oriented Modelling

Bo-Hsiang Tseng, Marek Rei, Paweł Budzianowski +3

Dialogue systems benefit greatly from optimizing on detailed annotations, such as transcribed utterances, internal dialogue state representations and dialogue act labels. However,…

cs.CL20191 cited

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

Bo-Hsiang Tseng, Paweł Budzianowski, Yen-Chen Wu +1

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. Thi…

cs.CL2019

Addressing Objects and Their Relations: The Conversational Entity Dialogue Model

Stefan Ultes, Paweł Budzianowski, Iñigo Casanueva +5

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.,…