Log In Sign Up

Modeling Intent, Dialog Policies and Response Adaptation for Goal-Oriented Interactions

by   Saurav Sahay, et al.

Building a machine learning driven spoken dialog system for goal-oriented interactions involves careful design of intents and data collection along with development of intent recognition models and dialog policy learning algorithms. The models should be robust enough to handle various user distractions during the interaction flow and should steer the user back into an engaging interaction for successful completion of the interaction. In this work, we have designed a goal-oriented interaction system where children can engage with agents for a series of interactions involving `Meet & Greet' and `Simon Says' game play. We have explored various feature extractors and models for improved intent recognition and looked at leveraging previous user and system interactions in novel ways with attention models. We have also looked at dialog adaptation methods for entrained response selection. Our bootstrapped models from limited training data perform better than many baseline approaches we have looked at for intent recognition and dialog action prediction.


page 1

page 2

page 3

page 4


Benchmarking Intent Detection for Task-Oriented Dialog Systems

Intent detection is a key component of modern goal-oriented dialog syste...

Assessing User Expertise in Spoken Dialog System Interactions

Identifying the level of expertise of its users is important for a syste...

A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog

Interest in dialog systems has grown substantially in the past decade. B...

NLU for Game-based Learning in Real: Initial Evaluations

Intelligent systems designed for play-based interactions should be conte...

Conversation Learner – A Machine Teaching Tool for Building Dialog Managers for Task-Oriented Dialog Systems

Traditionally, industry solutions for building a task-oriented dialog sy...

Dialog Intent Induction via Density-based Deep Clustering Ensemble

Existing task-oriented chatbots heavily rely on spoken language understa...

User Intent Classification using Memory Networks: A Comparative Analysis for a Limited Data Scenario

In this report, we provide a comparative analysis of different technique...