Papers by Natalie Parde
From Heart to Words: Generating Empathetic Responses via Integrated Figurative Language and Semantic Context Signals (2025.findings-acl)
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| Challenge: | Existing research on empathy generation focuses on understanding the emotions of the speaker rather than on how the responder conveys empathy. |
| Approach: | They propose to use figurative language and causal semantic context to facilitate targeted empathy generation in a mental health support domain. |
| Outcome: | The proposed approach achieves 7.6% improvement in BLEU, 36.7% reduction in Perplexity, and 7.6% increase in lexical diversity. |
Telling a Lie: Analyzing the Language of Information and Misinformation during Global Health Events (2022.lrec-1)
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| Challenge: | a new dataset is available to stimulate research on health misinformation . linguistic characteristics of health misinfonia are unique to COVID-19 and other events . |
| Approach: | They propose a new dataset that analyzes health misinformation at scale . it includes 2.8 million news articles and social media posts covering diseases . authors propose an annotation framework that allows for strong agreement between annotators . |
| Outcome: | The proposed dataset is based on 2.8 million news articles and social media posts spanning 1900s to present . it shows that the proposed model is robust and can be used to detect misinformation . |
Modeling Dialogue in Conversational Cognitive Health Screening Interviews (2020.lrec-1)
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| Challenge: | Dementia is one of the most pressing healthcare concerns as median age rises . a conversational agent capable of conducting cognitive health screening interviews could be an inexpensive, flexible, low-stress alternative . |
| Approach: | They propose an annotation schema for assigning dialogue act labels to utterances in patient-interviewer conversations collected as part of a clinically-validated cognitive health screening task. |
| Outcome: | The proposed system is characterized by high inter-annotator agreement and is able to perform clinically-validated cognitive health screening tasks. |
Towards Domain-Agnostic and Domain-Adaptive Dementia Detection from Spoken Language (2023.acl-long)
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| Challenge: | Domain adaptation (DA) techniques have been used to improve performance of NLP systems for healthcare tasks due to numerous complexities of data. |
| Approach: | They propose to use domain adaptation techniques to improve generalizability across diverse datasets for dementia detection. |
| Outcome: | The proposed model achieves a 22% increase in accuracy adapting from a conversational to task-oriented dataset compared to a jointly trained baseline. |
TweetTaglish: A Dataset for Investigating Tagalog-English Code-Switching (2022.lrec-1)
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| Challenge: | a large dataset is available to study Tagalog-English code-switching in low-resource settings. |
| Approach: | They propose to use a large dataset to investigate Tagalog-English code-switching . they use linguistic data from Tagalogue and Tagalit-English to investigate their results . |
| Outcome: | The proposed dataset achieves a strong performance benchmark for Tagalog-English code-switching. |
The AI Doctor Is In: A Survey of Task-Oriented Dialogue Systems for Healthcare Applications (2022.acl-long)
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| Challenge: | Task-oriented dialogue systems have been surveyed in the medical community from a non-technical perspective, but a systematic review from . a rigorous computational perspective has to date remained noticeably absent. |
| Approach: | They analyze 4070 papers on task-oriented dialogue systems for healthcare applications and identify gaps in their analysis. |
| Outcome: | The proposed system-level implementation details remain limited or underspecified, slowing the pace of innovation in this area. |
Pouring Your Heart Out: Investigating the Role of Figurative Language in Online Expressions of Empathy (2024.acl-long)
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| Challenge: | Empathy is a social mechanism used to support and strengthen emotional connection with others, including in online communities. |
| Approach: | They propose to use a subcategory of linguistic phenomena, figurative language, to detect online expressions of empathy. |
| Outcome: | The proposed model improves on the use of metaphor, idiom, and hyperbole in online expressions of empathy, with 0.942 and 0.809 F1 scores. |
SLaCAD: A Spoken Language Corpus for Early Alzheimer’s Disease Detection (2024.lrec-main)
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Shahla Farzana, Edoardo Stoppa, Alex Leow, Tamar Gollan, Raeanne Moore, David Salmon, Douglas Galasko, Erin Sundermann, Natalie Parde
| Challenge: | Recent studies show that cerebrospinal fluid (CSF) levels serve as useful early biomarkers for identifying early AD, but CSF biomarker collection is challenging. |
| Approach: | They propose to use speech data to identify early Alzheimer's disease (AD) trajectory to identify cognitive deficits in early disease stages. |
| Outcome: | The proposed dataset relates speech and speech characteristics with CSF and plasma biomarkers to clinical diagnoses, CSF levels, and biomarker scores. |
CareCorpus: A Corpus of Real-World Solution-Focused Caregiver Strategies for Personalized Pediatric Rehabilitation Service Design (2024.lrec-main)
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| Challenge: | Pediatric rehabilitation services focus on functional skills and participation, defined as attendance and involvement in home, school, and community activities. |
| Approach: | They propose to use a dataset of 780 real-world strategies written by caregivers to sort caregiver strategies for use in designing pediatric rehabilitation care plans. |
| Outcome: | The proposed model can be used to sort caregiver strategies for use in designing pediatric rehabilitation care plans. |
Identifying Medical Self-Disclosure in Online Communities (2021.naacl-main)
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| Challenge: | a new dataset of health-related posts from online social platforms is available for analysis . medical self-disclosure may be useful for early detection and treatment of medical issues . |
| Approach: | They propose to analyze medical self-disclosure in online health conversations . they release a dataset of health-related posts from online social platforms with high inter-annotator agreement . |
| Outcome: | The proposed model achieves an accuracy of 81.02% and sets a strong performance benchmark. |
CORI: CJKV Benchmark with Romanization Integration - a Step towards Cross-lingual Transfer beyond Textual Scripts (2024.lrec-main)
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| Challenge: | Naively assuming English as a source language may hinder cross-lingual transfer . despite recent advances in cross-linguistic research, most studies have restricted themselves to two major assumptions . |
| Approach: | They propose to integrate Romanized transcription beyond textual scripts to capture contact between these languages . they propose to use a benchmark dataset to further encourage in-depth studies of language contact . |
| Outcome: | The proposed method allows for enhanced cross-lingual representations and effective zero-shot cross-linguistic transfer. |
CareCorpus+: Expanding and Augmenting Caregiver Strategy Data to Support Pediatric Rehabilitation (2024.emnlp-main)
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| Challenge: | Existing studies on caregiver strategy classification in pediatric rehabilitation contexts are under-resourced and under-studied. |
| Approach: | They propose to manually categorized 4,037 caregiver strategies in a pediatric rehabilitation setting, and manually supplement target task data with publicly relevant child health forums. |
| Outcome: | The proposed method improves the quality of the dataset and shows that it performs well. |
Exploring Variation of Results from Different Experimental Conditions (2023.findings-acl)
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| Challenge: | Recent research has shown that reproducibility of NLP experiments is not guaranteed by arbitrary factors like random seed and different data splits. |
| Approach: | They propose to run the training and testing pipeline for three neural text simplification models under varying experimental conditions using the same data and train/dev/test set splits. |
| Outcome: | The proposed pipeline yields a large number of results for three neural text simplification models under varying experimental conditions. |
Reproducibility in Computational Linguistics: Is Source Code Enough? (2022.emnlp-main)
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| Challenge: | a recent study finds that source code releases leave much to be desired . authors can include small-scale experiments and explicit scripts to generate each result . |
| Approach: | They propose that conferences require self-contained artifacts to evaluate their reproducibility . authors suggest authors include small-scale experiments and explicit scripts to generate results . |
| Outcome: | The authors find that source code releases leave much to be desired . authors can include small-scale experiments and explicit scripts to generate each result . |
Humanistic Buddhism Corpus: A Challenging Domain-Specific Dataset of English Translations for Classical and Modern Chinese (2024.lrec-main)
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| Challenge: | Compared to existing machine translation datasets, HBC presents unique challenges . classical and modern Chinese texts are often translated in distant languages . |
| Approach: | They propose a dataset containing 80,000 Chinese-English parallel phrases extracted and translated from publications in the domain of Buddhism. |
| Outcome: | The Humanistic Buddhism Corpus (HBC) contains 80,000 parallel Chinese-English phrases extracted and translated from publications in the domain of Buddhism. |
Towards Intelligent Clinically-Informed Language Analyses of People with Bipolar Disorder and Schizophrenia (2022.findings-emnlp)
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| Challenge: | Existing studies on social media data have limited the extent to which they can produce meaningful or generalizable conclusions. |
| Approach: | They propose to use transcribed conversations with people with bipolar disorder and schizophrenia to create a large dataset of transcriptions. |
| Outcome: | The proposed dataset extracts 100+ temporal, sentiment, psycholinguistic, emotion, and lexical features and establishes classification validity. |
AcnEmpathize: A Dataset for Understanding Empathy in Dermatology Conversations (2024.lrec-main)
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| Challenge: | Existing studies on empathy and mental health-related corpora focus on broader contexts and lack domain specificity. |
| Approach: | They propose a dataset that captures empathy expressed in acne-related discussions from forum posts focused on its emotional and psychological effects. |
| Outcome: | The AcnEmpathize dataset shows that it performs well at empathy classification. |
Domain Adaptation via Prompt Learning for Alzheimer’s Detection (2024.findings-emnlp)
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| Challenge: | Existing attempts to fine-tune pre-trained language models for AD detection are limited by the small and disparate corpora of spoken language. |
| Approach: | They propose to use domain-adaptive prompt fine-tuning to optimize for AD detection by using AD classification loss as the training objective and spoken language corpora from a variety of language tasks. |
| Outcome: | The proposed approach achieves the highest detection rate with the highest-performing prompting paradigm and the domain-adaptive prompt fine-tuning paradigm. |
Towards Comprehensive Language Analysis for Clinically Enriched Spontaneous Dialogue (2024.lrec-main)
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| Challenge: | Contemporary NLP has progressed from feature-based classification to fine-tuning and prompt-based techniques . many of these techniques remain understudied in the context of real-world, clinically enriched spontaneous dialogue. |
| Approach: | They investigate the efficacy and overall performance of a range of NLP techniques on transcribed speech from patients with schizophrenia and other disorders. |
| Outcome: | The proposed methods are effective in analyzing transcribed speech from patients with schizophrenia and healthy controls taking a clinically-validated language test. |
Enriching Neural Models with Targeted Features for Dementia Detection (P19-2)
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| Challenge: | In the United States, adults over 65 are expected to comprise one-fifth of the population by 2030, and a larger proportion of the . population than those under 18 by 2035. |
| Approach: | They propose a neural model that takes into account both long language samples and hand-crafted linguistic features to distinguish between dementia affected and healthy patients. |
| Outcome: | The proposed model achieves an F1 score of 0.929 on the DementiaBank dataset and the state-of-the-art on the dataset. |
A Corpus of Metaphor Novelty Scores for Syntactically-Related Word Pairs (L18-1)
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| Challenge: | Existing data on metaphor novelty are limited, making it difficult to perform research on this topic. |
| Approach: | They propose to release a corpus of metaphor novelty scores for syntactically related word pairs . they establish a performance benchmark to which future researchers can compare . |
| Outcome: | The proposed corpus of metaphor novelty scores is compared to other datasets . it performs better than chance or nave strategies, the authors show . |
Demystifying Neural Fake News via Linguistic Feature-Based Interpretation (2022.coling-1)
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| Challenge: | Recent advances to neural fake news generators have made it difficult to understand how misinformation generated by these models may best be confronted. |
| Approach: | They conduct feature-based analysis to gain an interpretative understanding of the linguistic attributes that neural fake news generators may most effectively exploit. |
| Outcome: | The proposed models are compared with models trained on subsets of features and confronted with increasingly advanced neural fake news. |
What Clued the AI Doctor In? On the Influence of Data Source and Quality for Transformer-Based Medical Self-Disclosure Detection (2023.eacl-main)
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| Challenge: | Recognizing medical self-disclosure is important in many healthcare contexts, but it has been under-explored by the NLP community. |
| Approach: | They analyze a social media-based task to expand existing medical self-disclosure corpus and compare Transformer-based models to determine their merits. |
| Outcome: | The proposed dataset outperforms the state-of-the-art dataset for this task by 16.73%. |