Kristy Hollingshead


2019

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Proceedings of the Eighth Workshop on Speech and Language Processing for Assistive Technologies
Heidi Christensen | Kristy Hollingshead | Emily Prud’hommeaux | Frank Rudzicz | Keith Vertanen
Proceedings of the Eighth Workshop on Speech and Language Processing for Assistive Technologies

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Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology
Kate Niederhoffer | Kristy Hollingshead | Philip Resnik | Rebecca Resnik | Kate Loveys
Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology

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CLPsych 2019 Shared Task: Predicting the Degree of Suicide Risk in Reddit Posts
Ayah Zirikly | Philip Resnik | Özlem Uzuner | Kristy Hollingshead
Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology

The shared task for the 2019 Workshop on Computational Linguistics and Clinical Psychology (CLPsych’19) introduced an assessment of suicide risk based on social media postings, using data from Reddit to identify users at no, low, moderate, or severe risk. Two variations of the task focused on users whose posts to the r/SuicideWatch subreddit indicated they might be at risk; a third task looked at screening users based only on their more everyday (non-SuicideWatch) posts. We received submissions from 15 different teams, and the results provide progress and insight into the value of language signal in helping to predict risk level.

2017

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Characterization of Divergence in Impaired Speech of ALS Patients
Archna Bhatia | Bonnie Dorr | Kristy Hollingshead | Samuel L. Phillips | Barbara McKenzie
BioNLP 2017

Approximately 80% to 95% of patients with Amyotrophic Lateral Sclerosis (ALS) eventually develop speech impairments, such as defective articulation, slow laborious speech and hypernasality. The relationship between impaired speech and asymptomatic speech may be seen as a divergence from a baseline. This relationship can be characterized in terms of measurable combinations of phonological characteristics that are indicative of the degree to which the two diverge. We demonstrate that divergence measurements based on phonological characteristics of speech correlate with physiological assessments of ALS. Speech-based assessments offer benefits over commonly-used physiological assessments in that they are inexpensive, non-intrusive, and do not require trained clinical personnel for administering and interpreting the results.

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Proceedings of the Fourth Workshop on Computational Linguistics and Clinical Psychology — From Linguistic Signal to Clinical Reality
Kristy Hollingshead | Molly E. Ireland | Kate Loveys
Proceedings of the Fourth Workshop on Computational Linguistics and Clinical Psychology — From Linguistic Signal to Clinical Reality

2016

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Proceedings of the Third Workshop on Computational Linguistics and Clinical Psychology
Kristy Hollingshead | Lyle Ungar
Proceedings of the Third Workshop on Computational Linguistics and Clinical Psychology

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Crazy Mad Nutters: The Language of Mental Health
Jena D. Hwang | Kristy Hollingshead
Proceedings of the Third Workshop on Computational Linguistics and Clinical Psychology

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The Clinical Panel: Leveraging Psychological Expertise During NLP Research
Glen Coppersmith | Kristy Hollingshead | H. Andrew Schwartz | Molly Ireland | Rebecca Resnik | Kate Loveys | April Foreman | Loring Ingraham
Proceedings of the First Workshop on NLP and Computational Social Science

2015

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From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses
Glen Coppersmith | Mark Dredze | Craig Harman | Kristy Hollingshead
Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality

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Quantifying the Language of Schizophrenia in Social Media
Margaret Mitchell | Kristy Hollingshead | Glen Coppersmith
Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality

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CLPsych 2015 Shared Task: Depression and PTSD on Twitter
Glen Coppersmith | Mark Dredze | Craig Harman | Kristy Hollingshead | Margaret Mitchell
Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality

2012

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Finite-State Chart Constraints for Reduced Complexity Context-Free Parsing Pipelines
Brian Roark | Kristy Hollingshead | Nathan Bodenstab
Computational Linguistics, Volume 38, Issue 4 - December 2012

2011

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Unary Constraints for Efficient Context-Free Parsing
Nathan Bodenstab | Kristy Hollingshead | Brian Roark
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

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Noisy SMS Machine Translation in Low-Density Languages
Vladimir Eidelman | Kristy Hollingshead | Philip Resnik
Proceedings of the Sixth Workshop on Statistical Machine Translation

2010

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A Python Toolkit for Universal Transliteration
Ting Qian | Kristy Hollingshead | Su-youn Yoon | Kyoung-young Kim | Richard Sproat
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We describe ScriptTranscriber, an open source toolkit for extracting transliterations in comparable corpora from languages written in different scripts. The system includes various methods for extracting potential terms of interest from raw text, for providing guesses on the pronunciations of terms, and for comparing two strings as possible transliterations using both phonetic and temporal measures. The system works with any script in the Unicode Basic Multilingual Plane and is easily extended to include new modules. Given comparable corpora, such as newswire text, in a pair of languages that use different scripts, ScriptTranscriber provides an easy way to mine transliterations from the comparable texts. This is particularly useful for underresourced languages, where training data for transliteration may be lacking, and where it is thus hard to train good transliterators. ScriptTranscriber provides an open source package that allows for ready incorporation of more sophisticated modules ― e.g. a trained transliteration model for a particular language pair. ScriptTranscriber is available as part of the nltk contrib source tree at http://code.google.com/p/nltk/.

2009

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Linear Complexity Context-Free Parsing Pipelines via Chart Constraints
Brian Roark | Kristy Hollingshead
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics

2008

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Classifying Chart Cells for Quadratic Complexity Context-Free Inference
Brian Roark | Kristy Hollingshead
Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008)

2007

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Pipeline Iteration
Kristy Hollingshead | Brian Roark
Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics

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Syntactic complexity measures for detecting Mild Cognitive Impairment
Brian Roark | Margaret Mitchell | Kristy Hollingshead
Biological, translational, and clinical language processing

2005

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Comparing and Combining Finite-State and Context-Free Parsers
Kristy Hollingshead | Seeger Fisher | Brian Roark
Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing