Amanda Stent

Also published as: Amanda J. Stent, A. Stent


2020

pdf bib
An Annotated Dataset of Discourse Modes in Hindi Stories
Swapnil Dhanwal | Hritwik Dutta | Hitesh Nankani | Nilay Shrivastava | Yaman Kumar | Junyi Jessy Li | Debanjan Mahata | Rakesh Gosangi | Haimin Zhang | Rajiv Ratn Shah | Amanda Stent
Proceedings of the 12th Language Resources and Evaluation Conference

In this paper, we present a new corpus consisting of sentences from Hindi short stories annotated for five different discourse modes argumentative, narrative, descriptive, dialogic and informative. We present a detailed account of the entire data collection and annotation processes. The annotations have a very high inter-annotator agreement (0.87 k-alpha). We analyze the data in terms of label distributions, part of speech tags, and sentence lengths. We characterize the performance of various classification algorithms on this dataset and perform ablation studies to understand the nature of the linguistic models suitable for capturing the nuances of the embedded discourse structures in the presented corpus.

pdf bib
A Preliminary Exploration of GANs for Keyphrase Generation
Avinash Swaminathan | Haimin Zhang | Debanjan Mahata | Rakesh Gosangi | Rajiv Ratn Shah | Amanda Stent
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

We introduce a new keyphrase generation approach using Generative Adversarial Networks (GANs). For a given document, the generator produces a sequence of keyphrases, and the discriminator distinguishes between human-curated and machine-generated keyphrases. We evaluated this approach on standard benchmark datasets. We observed that our model achieves state-of-the-art performance in the generation of abstractive keyphrases and is comparable to the best performing extractive techniques. Although we achieve promising results using GANs, they are not significantly better than the state-of-the-art generative models. To our knowledge, this is one of the first works that use GANs for keyphrase generation. We present a detailed analysis of our observations and expect that these findings would help other researchers to further study the use of GANs for the task of keyphrase generation.

2019

pdf bib
Roll Call Vote Prediction with Knowledge Augmented Models
Pallavi Patil | Kriti Myer | Ronak Zala | Arpit Singh | Sheshera Mysore | Andrew McCallum | Adrian Benton | Amanda Stent
Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)

The official voting records of United States congresspeople are preserved as roll call votes. Prediction of voting behavior of politicians for whom no voting record exists, such as individuals running for office, is important for forecasting key political decisions. Prior work has relied on past votes cast to predict future votes, and thus fails to predict voting patterns for politicians without voting records. We address this by augmenting a prior state of the art model with multiple sources of external knowledge so as to enable prediction on unseen politicians. The sources of knowledge we use are news text and Freebase, a manually curated knowledge base. We propose augmentations based on unigram features for news text, and a knowledge base embedding method followed by a neural network composition for relations from Freebase. Empirical evaluation of these approaches indicate that the proposed models outperform the prior system for politicians with complete historical voting records by 1.0% point of accuracy (8.7% error reduction) and for politicians without voting records by 33.4% points of accuracy (66.7% error reduction). We also show that the knowledge base augmented approach outperforms the news text augmented approach by 4.2% points of accuracy.

pdf bib
Modeling Financial Analysts’ Decision Making via the Pragmatics and Semantics of Earnings Calls
Katherine Keith | Amanda Stent
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Every fiscal quarter, companies hold earnings calls in which company executives respond to questions from analysts. After these calls, analysts often change their price target recommendations, which are used in equity re- search reports to help investors make deci- sions. In this paper, we examine analysts’ decision making behavior as it pertains to the language content of earnings calls. We identify a set of 20 pragmatic features of analysts’ questions which we correlate with analysts’ pre-call investor recommendations. We also analyze the degree to which semantic and pragmatic features from an earnings call complement market data in predicting analysts’ post-call changes in price targets. Our results show that earnings calls are moderately predictive of analysts’ decisions even though these decisions are influenced by a number of other factors including private communication with company executives and market conditions. A breakdown of model errors indicates disparate performance on calls from different market sectors.

pdf bib
Proceedings of the Natural Legal Language Processing Workshop 2019
Nikolaos Aletras | Elliott Ash | Leslie Barrett | Daniel Chen | Adam Meyers | Daniel Preotiuc-Pietro | David Rosenberg | Amanda Stent
Proceedings of the Natural Legal Language Processing Workshop 2019

2018

pdf bib
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
Marilyn Walker | Heng Ji | Amanda Stent
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)

pdf bib
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
Marilyn Walker | Heng Ji | Amanda Stent
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)

2016

pdf bib
Humor in Collective Discourse: Unsupervised Funniness Detection in the New Yorker Cartoon Caption Contest
Dragomir Radev | Amanda Stent | Joel Tetreault | Aasish Pappu | Aikaterini Iliakopoulou | Agustin Chanfreau | Paloma de Juan | Jordi Vallmitjana | Alejandro Jaimes | Rahul Jha | Robert Mankoff
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

The New Yorker publishes a weekly captionless cartoon. More than 5,000 readers submit captions for it. The editors select three of them and ask the readers to pick the funniest one. We describe an experiment that compares a dozen automatic methods for selecting the funniest caption. We show that negative sentiment, human-centeredness, and lexical centrality most strongly match the funniest captions, followed by positive sentiment. These results are useful for understanding humor and also in the design of more engaging conversational agents in text and multimodal (vision+text) systems. As part of this work, a large set of cartoons and captions is being made available to the community.

pdf bib
Extractive Summarization under Strict Length Constraints
Yashar Mehdad | Amanda Stent | Kapil Thadani | Dragomir Radev | Youssef Billawala | Karolina Buchner
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In this paper we report a comparison of various techniques for single-document extractive summarization under strict length budgets, which is a common commercial use case (e.g. summarization of news articles by news aggregators). We show that, evaluated using ROUGE, numerous algorithms from the literature fail to beat a simple lead-based baseline for this task. However, a supervised approach with lightweight and efficient features improves over the lead-based baseline. Additional human evaluation demonstrates that the supervised approach also performs competitively with a commercial system that uses more sophisticated features.

pdf bib
A Low-Rank Approximation Approach to Learning Joint Embeddings of News Stories and Images for Timeline Summarization
William Yang Wang | Yashar Mehdad | Dragomir R. Radev | Amanda Stent
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

pdf bib
Task Lineages: Dialog State Tracking for Flexible Interaction
Sungjin Lee | Amanda Stent
Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue

pdf bib
The Role of Discourse Units in Near-Extractive Summarization
Junyi Jessy Li | Kapil Thadani | Amanda Stent
Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2015

pdf bib
The Cohort and Speechify Libraries for Rapid Construction of Speech Enabled Applications for Android
Tejaswi Kasturi | Haojian Jin | Aasish Pappu | Sungjin Lee | Beverley Harrison | Ramana Murthy | Amanda Stent
Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue

pdf bib
It Depends: Dependency Parser Comparison Using A Web-based Evaluation Tool
Jinho D. Choi | Joel Tetreault | Amanda Stent
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

2014

pdf bib
Proceedings of the EACL 2014 Workshop on Dialogue in Motion
Tiphaine Dalmas | Jana Götze | Joakim Gustafson | Srinivasan Janarthanam | Jan Kleindienst | Christian Mueller | Amanda Stent | Andreas Vlachos
Proceedings of the EACL 2014 Workshop on Dialogue in Motion

pdf bib
A Hybrid Approach to Multi-document Summarization of Opinions in Reviews
Giuseppe Di Fabbrizio | Amanda Stent | Robert Gaizauskas
Proceedings of the 8th International Natural Language Generation Conference (INLG)

2013

pdf bib
ATT1: Temporal Annotation Using Big Windows and Rich Syntactic and Semantic Features
Hyuckchul Jung | Amanda Stent
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)

2012

pdf bib
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Gary Geunbae Lee | Jonathan Ginzburg | Claire Gardent | Amanda Stent
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

pdf bib
After Dialog Went Pervasive: Separating Dialog Behavior Modeling and Task Modeling
Amanda Stent
NAACL-HLT Workshop on Future directions and needs in the Spoken Dialog Community: Tools and Data (SDCTD 2012)

2011

pdf bib
The First Surface Realisation Shared Task: Overview and Evaluation Results
Anja Belz | Mike White | Dominic Espinosa | Eric Kow | Deirdre Hogan | Amanda Stent
Proceedings of the 13th European Workshop on Natural Language Generation

pdf bib
ATT-0: Submission to Generation Challenges 2011 Surface Realization Shared Task
Amanda Stent
Proceedings of the 13th European Workshop on Natural Language Generation

2010

pdf bib
Finding Common Ground: Towards a Surface Realisation Shared Task
Anja Belz | Mike White | Josef van Genabith | Deirdre Hogan | Amanda Stent
Proceedings of the 6th International Natural Language Generation Conference

2009

pdf bib
Predicting Concept Types in User Corrections in Dialog
Svetlana Stoyanchev | Amanda Stent
Proceedings of SRSL 2009, the 2nd Workshop on Semantic Representation of Spoken Language

pdf bib
Concept Form Adaptation in Human-Computer Dialog
Svetlana Stoyanchev | Amanda Stent
Proceedings of the SIGDIAL 2009 Conference

pdf bib
Evaluating Automatic Extraction of Rules for Sentence Plan Construction
Amanda Stent | Martin Molina
Proceedings of the SIGDIAL 2009 Conference

pdf bib
Incremental Parsing Models for Dialog Task Structure
Srinivas Bangalore | Amanda Stent
Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009)

pdf bib
Geo-Centric Language Models for Local Business Voice Search
Amanda Stent | Ilija Zeljković | Diamantino Caseiro | Jay Wilpon
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics

pdf bib
Lexical and Syntactic Adaptation and Their Impact in Deployed Spoken Dialog Systems
Svetlana Stoyanchev | Amanda Stent
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers

pdf bib
Determining the position of adverbial phrases in English
Huayan Zhong | Amanda Stent
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers

2008

pdf bib
Referring Expression Generation Using Speaker-based Attribute Selection and Trainable Realization (ATTR)
Giuseppe Di Fabbrizio | Amanda J. Stent | Srinivas Bangalore
Proceedings of the Fifth International Natural Language Generation Conference

pdf bib
Trainable Speaker-Based Referring Expression Generation
Giuseppe Di Fabbrizio | Amanda Stent | Srinivas Bangalore
CoNLL 2008: Proceedings of the Twelfth Conference on Computational Natural Language Learning

2007

pdf bib
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)

pdf bib
RavenCalendar: A Multimodal Dialog System for Managing a Personal Calendar
Svetlana Stenchikova | Basia Mucha | Sarah Hoffman | Amanda Stent
Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT)

pdf bib
Measuring Adaptation Between Dialogs
Svetlana Stenchikova | Amanda Stent
Proceedings of the 8th SIGdial Workshop on Discourse and Dialogue

2006

pdf bib
Learning the Structure of Task-Driven Human-Human Dialogs
Srinivas Bangalore | Giuseppe Di Fabbrizio | Amanda Stent
Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics

2005

pdf bib
Two Diverse Systems Built using Generic Components for Spoken Dialogue (Recent Progress on TRIPS)
James Allen | George Ferguson | Amanda Stent | Scott Stoness | Mary Swift | Lucian Galescu | Nathan Chambers | Ellen Campana | Gregory Aist
Proceedings of the ACL Interactive Poster and Demonstration Sessions

2004

pdf bib
Trainable Sentence Planning for Complex Information Presentations in Spoken Dialog Systems
Amanda Stent | Rashmi Prasad | Marilyn Walker
Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04)

2002

pdf bib
Speech-Plans: Generating Evaluative Responses in Spoken Dialogue
M. A. Walker | S. Whittaker | A. Stent | P. Maloor | J. D. Moore | M. Johnston | G. Vasireddy
Proceedings of the International Natural Language Generation Conference

pdf bib
MATCH: An Architecture for Multimodal Dialogue Systems
Michael Johnston | Srinivas Bangalore | Gunaranjan Vasireddy | Amanda Stent | Patrick Ehlen | Marilyn Walker | Steve Whittaker | Preetam Maloor
Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics

2000

pdf bib
TRIPS- 911 System Demonstration
James Allen | Donna Byron | Dave Costello | Myroslava Dzikovska | George Ferguson | Lucian Galescu | Amanda Stent
ANLP-NAACL 2000 Workshop: Conversational Systems

pdf bib
Rhetorical Structure in Dialog
Amanda Stent
INLG’2000 Proceedings of the First International Conference on Natural Language Generation

1999

pdf bib
The CommandTalk Spoken Dialogue System
Amanda Stent | John Dowding | Jean Mark Gawron | Elizabeth Owen Bratt | Robert Moore
Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics

1998

pdf bib
A Preliminary Model of Centering in Dialog
D. Byron | A. Stent
COLING 1998 Volume 2: The 17th International Conference on Computational Linguistics

pdf bib
A Preliminary Model of Centering in Dialog
Donna Byron | Amanda Stent
36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, Volume 2

Search
Co-authors