Search Results for author: Simon Keizer

Found 10 papers, 3 papers with code

Dialogue Strategy Adaptation to New Action Sets Using Multi-dimensional Modelling

no code implementations14 Apr 2022 Simon Keizer, Norbert Braunschweiler, Svetlana Stoyanchev, Rama Doddipatla

A major bottleneck for building statistical spoken dialogue systems for new domains and applications is the need for large amounts of training data.

Dialogue Management Spoken Dialogue Systems +1

A study on cross-corpus speech emotion recognition and data augmentation

no code implementations10 Jan 2022 Norbert Braunschweiler, Rama Doddipatla, Simon Keizer, Svetlana Stoyanchev

Models trained on mixed corpora can be more stable in mismatched contexts, and the performance reductions range from 1 to 8% when compared with single corpus models in matched conditions.

Data Augmentation Speech Emotion Recognition

Action State Update Approach to Dialogue Management

no code implementations9 Nov 2020 Svetlana Stoyanchev, Simon Keizer, Rama Doddipatla

Utterance interpretation is one of the main functions of a dialogue manager, which is the key component of a dialogue system.

Active Learning Dialogue Management +1

The ISO Standard for Dialogue Act Annotation, Second Edition

no code implementations LREC 2020 Harry Bunt, Volha Petukhova, Emer Gilmartin, Catherine Pelachaud, Alex Fang, Simon Keizer, Laurent Pr{\'e}vot

ISO standard 24617-2 for dialogue act annotation, established in 2012, has in the past few years been used both in corpus annotation and in the design of components for spoken and multimodal dialogue systems.

User Evaluation of a Multi-dimensional Statistical Dialogue System

1 code implementation WS 2019 Simon Keizer, Ondřej Dušek, Xingkun Liu, Verena Rieser

We present the first complete spoken dialogue system driven by a multi-dimensional statistical dialogue manager.

Strategic Dialogue Management via Deep Reinforcement Learning

1 code implementation25 Nov 2015 Heriberto Cuayáhuitl, Simon Keizer, Oliver Lemon

This paper describes a successful application of Deep Reinforcement Learning (DRL) for training intelligent agents with strategic conversational skills, in a situated dialogue setting.

Dialogue Management reinforcement-learning

Cannot find the paper you are looking for? You can Submit a new open access paper.