Amit Dubey


2019

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Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset
Bill Byrne | Karthik Krishnamoorthi | Chinnadhurai Sankar | Arvind Neelakantan | Ben Goodrich | Daniel Duckworth | Semih Yavuz | Amit Dubey | Kyu-Young Kim | Andy Cedilnik
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

A significant barrier to progress in data-driven approaches to building dialog systems is the lack of high quality, goal-oriented conversational data. To help satisfy this elementary requirement, we introduce the initial release of the Taskmaster-1 dataset which includes 13,215 task-based dialogs comprising six domains. Two procedures were used to create this collection, each with unique advantages. The first involves a two-person, spoken “Wizard of Oz” (WOz) approach in which trained agents and crowdsourced workers interact to complete the task while the second is “self-dialog” in which crowdsourced workers write the entire dialog themselves. We do not restrict the workers to detailed scripts or to a small knowledge base and hence we observe that our dataset contains more realistic and diverse conversations in comparison to existing datasets. We offer several baseline models including state of the art neural seq2seq architectures with benchmark performance as well as qualitative human evaluations. Dialogs are labeled with API calls and arguments, a simple and cost effective approach which avoids the requirement of complex annotation schema. The layer of abstraction between the dialog model and the service provider API allows for a given model to interact with multiple services that provide similar functionally. Finally, the dataset will evoke interest in written vs. spoken language, discourse patterns, error handling and other linguistic phenomena related to dialog system research, development and design.

2011

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A Model of Discourse Predictions in Human Sentence Processing
Amit Dubey | Frank Keller | Patrick Sturt
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

2010

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The Influence of Discourse on Syntax: A Psycholinguistic Model of Sentence Processing
Amit Dubey
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

2007

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Using Foreign Inclusion Detection to Improve Parsing Performance
Beatrice Alex | Amit Dubey | Frank Keller
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)

2006

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Integrating Syntactic Priming into an Incremental Probabilistic Parser, with an Application to Psycholinguistic Modeling
Amit Dubey | Frank Keller | Patrick Sturt
Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics

2005

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What to Do When Lexicalization Fails: Parsing German with Suffix Analysis and Smoothing
Amit Dubey
Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05)

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Parallelism in Coordination as an Instance of Syntactic Priming: Evidence from Corpus-based Modeling
Amit Dubey | Patrick Sturt | Frank Keller
Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing

2003

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Antecedent Recovery: Experiments with a Trace Tagger
Péter Dienes | Amit Dubey
Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing

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Probabilistic Parsing for German Using Sister-Head Dependencies
Amit Dubey | Frank Keller
Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics

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Deep Syntactic Processing by Combining Shallow Methods
Péter Dienes | Amit Dubey
Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics