Alquist 4.0: Towards Social Intelligence Using Generative Models and Dialogue Personalization

09/16/2021
by   Jakub Konrád, et al.
0

The open domain-dialogue system Alquist has a goal to conduct a coherent and engaging conversation that can be considered as one of the benchmarks of social intelligence. The fourth version of the system, developed within the Alexa Prize Socialbot Grand Challenge 4, brings two main innovations. The first addresses coherence, and the second addresses the engagingness of the conversation. For innovations regarding coherence, we propose a novel hybrid approach combining hand-designed responses and a generative model. The proposed approach utilizes hand-designed dialogues, out-of-domain detection, and a neural response generator. Hand-designed dialogues walk the user through high-quality conversational flows. The out-of-domain detection recognizes that the user diverges from the predefined flow and prevents the system from producing a scripted response that might not make sense for unexpected user input. Finally, the neural response generator generates a response based on the context of the dialogue that correctly reacts to the unexpected user input and returns the dialogue to the boundaries of hand-designed dialogues. The innovations for engagement that we propose are mostly inspired by the famous exploration-exploitation dilemma. To conduct an engaging conversation with the dialogue partners, one has to learn their preferences and interests – exploration. Moreover, to engage the partner, we have to utilize the knowledge we have already learned – exploitation. In this work, we present the principles and inner workings of individual components of the open-domain dialogue system Alquist developed within the Alexa Prize Socialbot Grand Challenge 4 and the experiments we have conducted to evaluate them.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/25/2022

Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agent

We present Chirpy Cardinal, an open-domain social chatbot. Aiming to be ...
research
06/12/2022

Grounding in social media: An approach to building a chit-chat dialogue model

Building open-domain dialogue systems capable of rich human-like convers...
research
05/06/2021

A Unified Pre-training Framework for Conversational AI

In this work, we explore the application of PLATO-2 on various dialogue ...
research
08/28/2021

Distilling the Knowledge of Large-scale Generative Models into Retrieval Models for Efficient Open-domain Conversation

Despite the remarkable performance of large-scale generative models in o...
research
10/31/2021

An Approach to Inference-Driven Dialogue Management within a Social Chatbot

We present a chatbot implementing a novel dialogue management approach b...
research
12/02/2021

Evaluator for Emotionally Consistent Chatbots

One challenge for evaluating current sequence- or dialogue-level chatbot...
research
04/18/2018

Alquist: The Alexa Prize Socialbot

This paper describes a new open domain dialogue system Alquist developed...

Please sign up or login with your details

Forgot password? Click here to reset