Jason D. Williams

Also published as: Jason Williams


2020

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Improving Human-Labeled Data through Dynamic Automatic Conflict Resolution
David Q. Sun | Hadas Kotek | Christopher Klein | Mayank Gupta | William Li | Jason D. Williams
Proceedings of the 28th International Conference on Computational Linguistics

This paper develops and implements a scalable methodology for (a) estimating the noisiness of labels produced by a typical crowdsourcing semantic annotation task, and (b) reducing the resulting error of the labeling process by as much as 20-30% in comparison to other common labeling strategies. Importantly, this new approach to the labeling process, which we name Dynamic Automatic Conflict Resolution (DACR), does not require a ground truth dataset and is instead based on inter-project annotation inconsistencies. This makes DACR not only more accurate but also available to a broad range of labeling tasks. In what follows we present results from a text classification task performed at scale for a commercial personal assistant, and evaluate the inherent ambiguity uncovered by this annotation strategy as compared to other common labeling strategies.

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Conversational Semantic Parsing for Dialog State Tracking
Jianpeng Cheng | Devang Agrawal | Héctor Martínez Alonso | Shruti Bhargava | Joris Driesen | Federico Flego | Dain Kaplan | Dimitri Kartsaklis | Lin Li | Dhivya Piraviperumal | Jason D. Williams | Hong Yu | Diarmuid Ó Séaghdha | Anders Johannsen
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

We consider a new perspective on dialog state tracking (DST), the task of estimating a user’s goal through the course of a dialog. By formulating DST as a semantic parsing task over hierarchical representations, we can incorporate semantic compositionality, cross-domain knowledge sharing and co-reference. We present TreeDST, a dataset of 27k conversations annotated with tree-structured dialog states and system acts. We describe an encoder-decoder framework for DST with hierarchical representations, which leads to ~20% improvement over state-of-the-art DST approaches that operate on a flat meaning space of slot-value pairs.

2017

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Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning
Jason D. Williams | Kavosh Asadi | Geoffrey Zweig
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

End-to-end learning of recurrent neural networks (RNNs) is an attractive solution for dialog systems; however, current techniques are data-intensive and require thousands of dialogs to learn simple behaviors. We introduce Hybrid Code Networks (HCNs), which combine an RNN with domain-specific knowledge encoded as software and system action templates. Compared to existing end-to-end approaches, HCNs considerably reduce the amount of training data required, while retaining the key benefit of inferring a latent representation of dialog state. In addition, HCNs can be optimized with supervised learning, reinforcement learning, or a mixture of both. HCNs attain state-of-the-art performance on the bAbI dialog dataset (Bordes and Weston, 2016), and outperform two commercially deployed customer-facing dialog systems at our company.

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Demonstration of interactive teaching for end-to-end dialog control with hybrid code networks
Jason D. Williams | Lars Liden
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue

This is a demonstration of interactive teaching for practical end-to-end dialog systems driven by a recurrent neural network. In this approach, a developer teaches the network by interacting with the system and providing on-the-spot corrections. Once a system is deployed, a developer can also correct mistakes in logged dialogs. This demonstration shows both of these teaching methods applied to dialog systems in three domains: pizza ordering, restaurant information, and weather forecasts.

2015

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Fast and easy language understanding for dialog systems with Microsoft Language Understanding Intelligent Service (LUIS)
Jason D. Williams | Eslam Kamal | Mokhtar Ashour | Hani Amr | Jessica Miller | Geoff Zweig
Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2014

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Discovering Latent Structure in Task-Oriented Dialogues
Ke Zhai | Jason D. Williams
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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The Second Dialog State Tracking Challenge
Matthew Henderson | Blaise Thomson | Jason D. Williams
Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)

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Web-style ranking and SLU combination for dialog state tracking
Jason D. Williams
Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)

2013

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Proceedings of the SIGDIAL 2013 Conference
Maxine Eskenazi | Michael Strube | Barbara Di Eugenio | Jason D. Williams
Proceedings of the SIGDIAL 2013 Conference

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Continuously Predicting and Processing Barge-in During a Live Spoken Dialogue Task
Ethan Selfridge | Iker Arizmendi | Peter Heeman | Jason Williams
Proceedings of the SIGDIAL 2013 Conference

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The Dialog State Tracking Challenge
Jason Williams | Antoine Raux | Deepak Ramachandran | Alan Black
Proceedings of the SIGDIAL 2013 Conference

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Multi-domain learning and generalization in dialog state tracking
Jason Williams
Proceedings of the SIGDIAL 2013 Conference

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Discriminative state tracking for spoken dialog systems
Angeliki Metallinou | Dan Bohus | Jason Williams
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

2012

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Integrating Incremental Speech Recognition and POMDP-Based Dialogue Systems
Ethan O. Selfridge | Iker Arizmendi | Peter A. Heeman | Jason D. Williams
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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A belief tracking challenge task for spoken dialog systems
Jason Williams
NAACL-HLT Workshop on Future directions and needs in the Spoken Dialog Community: Tools and Data (SDCTD 2012)

2011

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Spoken Dialog Challenge 2010: Comparison of Live and Control Test Results
Alan W Black | Susanne Burger | Alistair Conkie | Helen Hastie | Simon Keizer | Oliver Lemon | Nicolas Merigaud | Gabriel Parent | Gabriel Schubiner | Blaise Thomson | Jason D. Williams | Kai Yu | Steve Young | Maxine Eskenazi
Proceedings of the SIGDIAL 2011 Conference

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Stability and Accuracy in Incremental Speech Recognition
Ethan Selfridge | Iker Arizmendi | Peter Heeman | Jason Williams
Proceedings of the SIGDIAL 2011 Conference

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An Empirical Evaluation of a Statistical Dialog System in Public Use
Jason Williams
Proceedings of the SIGDIAL 2011 Conference

2009

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Estimating Probability of Correctness for ASR N-Best Lists
Jason Williams | Suhrid Balakrishnan
Proceedings of the SIGDIAL 2009 Conference

2008

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Using Automatically Transcribed Dialogs to Learn User Models in a Spoken Dialog System
Umar Syed | Jason Williams
Proceedings of ACL-08: HLT, Short Papers

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Demonstration of a POMDP Voice Dialer
Jason Williams
Proceedings of the ACL-08: HLT Demo Session

2007

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Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT)
Bob Carpenter | Amanda Stent | Jason D. Williams
Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT)

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Applying POMDPs to Dialog Systems in the Troubleshooting Domain
Jason Williams
Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies

2005

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Partially Observable Markov Decision Processes with Continuous Observations for Dialogue Management
Jason D. Williams | Pascal Poupart | Steve Young
Proceedings of the 6th SIGdial Workshop on Discourse and Dialogue

2003

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Using Wizard-of-Oz simulations to bootstrap Reinforcement - Learning based dialog management systems
Jason D. Williams | Steve Young
Proceedings of the Fourth SIGdial Workshop of Discourse and Dialogue