75 citations · 214 across the 27 of their papers we have counts for
8 papers · 1 filter
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,…
Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset
Bill Byrne, Karthik Krishnamoorthi, Chinnadhurai Sankar +7
A significant barrier to progress in data-driven approaches to building dialog systems is the lack of high quality, goal-oriented conversational data. To help satisfy this elementa…
On NMT Search Errors and Model Errors: Cat Got Your Tongue?
Felix Stahlberg, Bill Byrne
We report on search errors and model errors in neural machine translation (NMT). We present an exact inference procedure for neural sequence models based on a combination of beam s…
The CUED's Grammatical Error Correction Systems for BEA-2019
Felix Stahlberg, Bill Byrne
We describe two entries from the Cambridge University Engineering Department to the BEA 2019 Shared Task on grammatical error correction. Our submission to the low-resource track i…
UCAM Biomedical translation at WMT19: Transfer learning multi-domain ensembles
Danielle Saunders, Felix Stahlberg, Bill Byrne
The 2019 WMT Biomedical translation task involved translating Medline abstracts. We approached this using transfer learning to obtain a series of strong neural models on distinct d…
Cued@wmt19:ewc&lms
Felix Stahlberg, Danielle Saunders, Adria de Gispert +1
Two techniques provide the fabric of the Cambridge University Engineering Department's (CUED) entry to the WMT19 evaluation campaign: elastic weight consolidation (EWC) and differe…
Domain Adaptive Inference for Neural Machine Translation
Danielle Saunders, Felix Stahlberg, Adria de Gispert +1
We investigate adaptive ensemble weighting for Neural Machine Translation, addressing the case of improving performance on a new and potentially unknown domain without sacrificing…
Neural Grammatical Error Correction with Finite State Transducers
Felix Stahlberg, Christopher Bryant, Bill Byrne
Grammatical error correction (GEC) is one of the areas in natural language processing in which purely neural models have not yet superseded more traditional symbolic models. Hybrid…