An Ensemble Model with Ranking for Social Dialogue

Ioannis Papaioannou, Amanda Cercas Curry, Jose Part, Igor Shalyminov, Xu Xinnuo, Yanchao Yu, Ondrej Dusek, Verena Rieser, Oliver Lemon

Research output: Contribution to conferencePaper

Abstract

Open-domain social dialogue is one of the long-standing goals of Artificial Intelligence. This year, the Amazon Alexa Prize challenge was announced for the first time, where real customers get to rate systems developed by leading universities worldwide. The aim of the challenge is to converse “coherently and engagingly with humans on popular topics for 20 minutes”. We describe our Alexa Prize system (called ‘Alana’) consisting of an ensemble of bots, combining rule-based and machine learning systems, and using a contextual ranking mechanism to choose a system response. The ranker was trained on real user feedback received during the competition, where we address the problem of how to train on the noisy and sparse feedback obtained during the competition.
Original languageEnglish
Publication statusPublished - 2017
EventNIPS 2017 Conversational AI Workshop - Long Beach Convention Center, Long Beach, United States
Duration: 8 Dec 20178 Dec 2017

Workshop

WorkshopNIPS 2017 Conversational AI Workshop
CountryUnited States
CityLong Beach
Period8/12/178/12/17

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Artificial intelligence

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Papaioannou, I., Cercas Curry, A., Part, J., Shalyminov, I., Xinnuo, X., Yu, Y., ... Lemon, O. (2017). An Ensemble Model with Ranking for Social Dialogue. Paper presented at NIPS 2017 Conversational AI Workshop, Long Beach, United States.
Papaioannou, Ioannis ; Cercas Curry, Amanda ; Part, Jose ; Shalyminov, Igor ; Xinnuo, Xu ; Yu, Yanchao ; Dusek, Ondrej ; Rieser, Verena ; Lemon, Oliver. / An Ensemble Model with Ranking for Social Dialogue. Paper presented at NIPS 2017 Conversational AI Workshop, Long Beach, United States.
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title = "An Ensemble Model with Ranking for Social Dialogue",
abstract = "Open-domain social dialogue is one of the long-standing goals of Artificial Intelligence. This year, the Amazon Alexa Prize challenge was announced for the first time, where real customers get to rate systems developed by leading universities worldwide. The aim of the challenge is to converse “coherently and engagingly with humans on popular topics for 20 minutes”. We describe our Alexa Prize system (called ‘Alana’) consisting of an ensemble of bots, combining rule-based and machine learning systems, and using a contextual ranking mechanism to choose a system response. The ranker was trained on real user feedback received during the competition, where we address the problem of how to train on the noisy and sparse feedback obtained during the competition.",
author = "Ioannis Papaioannou and {Cercas Curry}, Amanda and Jose Part and Igor Shalyminov and Xu Xinnuo and Yanchao Yu and Ondrej Dusek and Verena Rieser and Oliver Lemon",
year = "2017",
language = "English",
note = "NIPS 2017 Conversational AI Workshop ; Conference date: 08-12-2017 Through 08-12-2017",

}

Papaioannou, I, Cercas Curry, A, Part, J, Shalyminov, I, Xinnuo, X, Yu, Y, Dusek, O, Rieser, V & Lemon, O 2017, 'An Ensemble Model with Ranking for Social Dialogue', Paper presented at NIPS 2017 Conversational AI Workshop, Long Beach, United States, 8/12/17 - 8/12/17.

An Ensemble Model with Ranking for Social Dialogue. / Papaioannou, Ioannis; Cercas Curry, Amanda; Part, Jose; Shalyminov, Igor; Xinnuo, Xu; Yu, Yanchao; Dusek, Ondrej; Rieser, Verena; Lemon, Oliver.

2017. Paper presented at NIPS 2017 Conversational AI Workshop, Long Beach, United States.

Research output: Contribution to conferencePaper

TY - CONF

T1 - An Ensemble Model with Ranking for Social Dialogue

AU - Papaioannou, Ioannis

AU - Cercas Curry, Amanda

AU - Part, Jose

AU - Shalyminov, Igor

AU - Xinnuo, Xu

AU - Yu, Yanchao

AU - Dusek, Ondrej

AU - Rieser, Verena

AU - Lemon, Oliver

PY - 2017

Y1 - 2017

N2 - Open-domain social dialogue is one of the long-standing goals of Artificial Intelligence. This year, the Amazon Alexa Prize challenge was announced for the first time, where real customers get to rate systems developed by leading universities worldwide. The aim of the challenge is to converse “coherently and engagingly with humans on popular topics for 20 minutes”. We describe our Alexa Prize system (called ‘Alana’) consisting of an ensemble of bots, combining rule-based and machine learning systems, and using a contextual ranking mechanism to choose a system response. The ranker was trained on real user feedback received during the competition, where we address the problem of how to train on the noisy and sparse feedback obtained during the competition.

AB - Open-domain social dialogue is one of the long-standing goals of Artificial Intelligence. This year, the Amazon Alexa Prize challenge was announced for the first time, where real customers get to rate systems developed by leading universities worldwide. The aim of the challenge is to converse “coherently and engagingly with humans on popular topics for 20 minutes”. We describe our Alexa Prize system (called ‘Alana’) consisting of an ensemble of bots, combining rule-based and machine learning systems, and using a contextual ranking mechanism to choose a system response. The ranker was trained on real user feedback received during the competition, where we address the problem of how to train on the noisy and sparse feedback obtained during the competition.

M3 - Paper

ER -

Papaioannou I, Cercas Curry A, Part J, Shalyminov I, Xinnuo X, Yu Y et al. An Ensemble Model with Ranking for Social Dialogue. 2017. Paper presented at NIPS 2017 Conversational AI Workshop, Long Beach, United States.