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20182022
most citedTransferable Dialogue Systems and User Simulators

2 citations · 2 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CL2022

Biased Self-supervised learning for ASR

Florian L. Kreyssig, Yangyang Shi, Jinxi Guo +3

Self-supervised learning via masked prediction pre-training (MPPT) has shown impressive performance on a range of speech-processing tasks. This paper proposes a method to bias self…

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.CL2018

Variational Cross-domain Natural Language Generation for Spoken Dialogue Systems

Bo-Hsiang Tseng, Florian Kreyssig, Pawel Budzianowski +4

Cross-domain natural language generation (NLG) is still a difficult task within spoken dialogue modelling. Given a semantic representation provided by the dialogue manager, the lan…

cs.CL2018

Neural User Simulation for Corpus-based Policy Optimisation for Spoken Dialogue Systems

Florian Kreyssig, Inigo Casanueva, Pawel Budzianowski +1

User Simulators are one of the major tools that enable offline training of task-oriented dialogue systems. For this task the Agenda-Based User Simulator (ABUS) is often used. The A…

cs.CL2018

Improved TDNNs using Deep Kernels and Frequency Dependent Grid-RNNs

Florian Kreyssig, Chao Zhang, Philip Woodland

Time delay neural networks (TDNNs) are an effective acoustic model for large vocabulary speech recognition. The strength of the model can be attributed to its ability to effectivel…