Papers by Verónica Pérez-Rosas
PAIR: Prompt-Aware margIn Ranking for Counselor Reflection Scoring in Motivational Interviewing (2022.emnlp-main)
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| Challenge: | Existing approaches to provide constructive feedback to counselors are limited by the time and cost involved. |
| Approach: | They propose a system that takes as input a client prompt and a counselor response and outputs a score indicating the level of reflection in the counselor response. |
| Outcome: | The proposed model outperforms baselines on different metrics and can be used to provide useful feedback to counseling trainees. |
Compositional Demographic Word Embeddings (2020.emnlp-main)
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| Challenge: | Word embeddings are usually derived from corpora containing text from many individuals . however, they cannot account for user-specific word preferences, such as using the same word in different ways across contexts. |
| Approach: | They propose a new form of personalized word embeddings that use demographic-specific word representations derived compositionally from full or partial demographic information for a user. |
| Outcome: | The proposed representations outperform generic representations on two English language tasks. |
Exploring the Value of Personalized Word Embeddings (2020.coling-main)
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| Challenge: | a subset of words belonging to specific psycholinguistic categories vary more in their representations across users . combining generic and personalized word embeddings yields the best performance . |
| Approach: | They propose personalized word embeddings and compare their performance to generic ones . they show that personalized word representations can be leveraged for improved performance . |
| Outcome: | The proposed model can be used for authorship attribution. |
Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper) (P19-1)
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Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, Roger Zimmermann, Rada Mihalcea, Soujanya Poria
| Challenge: | sarcasm is often expressed through multiple verbal and non-verbal cues, such as a change of tone, overemphasis, drawn-out syllables, or a straight looking face. |
| Approach: | They propose to use multimodal cues to improve sarcasm detection using audiovisual utterances annotated with sarcasm labels to improve the accuracy. |
| Outcome: | The proposed dataset reduces the error rate of sarcasm detection by 12.9% . it is based on audiovisual utterances annotated with sarcasm labels . |
Exploring Self-Identified Counseling Expertise in Online Support Forums (2021.findings-acl)
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Allison Lahnala, Yuntian Zhao, Charles Welch, Jonathan K. Kummerfeld, Lawrence C An, Kenneth Resnicow, Rada Mihalcea, Verónica Pérez-Rosas
| Challenge: | Increasing number of people engage in online health forums, making it important to understand the quality of the advice they receive. |
| Approach: | They examine the role of expertise in responses to help-seeking posts . they find that a classifier can distinguish between peer and self-identified mental health professionals' interactions . |
| Outcome: | The findings show that experts' language use differs between groups, and that their comments engage the support-seeker further. |
Inferring Social Media Users’ Mental Health Status from Multimodal Information (2020.lrec-1)
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| Challenge: | In the United States alone, one in every four adults suffers from a mental health condition, making mental health a pressing concern. |
| Approach: | They propose to use multimodal cues present in social media posts to predict mental health status by analyzing language, visual, and metadata cue data. |
| Outcome: | The proposed approach improves the performance of the classification task compared to using one modality at a time and can provide important cues into a user’s mental status. |
What Makes a Good Counselor? Learning to Distinguish between High-quality and Low-quality Counseling Conversations (P19-1)
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| Challenge: | Qualitative counseling relies on active collaboration between clients and counselors . |
| Approach: | They propose to use linguistic features to capture differences between high- and low-quality counseling conversations to build automatic classifiers that can predict counseling quality with accuracies of up to 88%. |
| Outcome: | The proposed model can predict counseling quality with accuracies of up to 88%. |
Biased TextRank: Unsupervised Graph-Based Content Extraction (2020.coling-main)
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| Challenge: | TextRank ranks text spans according to their importance for language processing tasks and their relevance to an input “focus.” |
| Approach: | They propose a graph-based content extraction method inspired by TextRank that ranks text spans according to their importance for language processing tasks and according to relevance to an input “focus.” |
| Outcome: | The proposed method improves on two different datasets by significant ROUGE-N score margins. |
Analyzing the Quality of Counseling Conversations: the Tell-Tale Signs of High-quality Counseling (L18-1)
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| Challenge: | Behavioral and mental health disorders are the most costly and prevalent conditions worldwide. |
| Approach: | They propose to use a dataset to analyze counseling interactions by using aspects such as mirroring, empathy, and reflective listening to build text-based classifiers. |
| Outcome: | The proposed dataset can be used to build text-based classifiers able to predict the overall quality of a counseling conversation and provide insights into the linguistic differences between low-quality and high-quality counseling. |
Automatic Detection of Fake News (C18-1)
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| Challenge: | a growing number of fake news detection tools are needed to identify trustworthy news sources. |
| Approach: | They propose to use two novel datasets to automate the identification of fake news . they propose learning experiments to build accurate fake news detectors . |
| Outcome: | The proposed algorithms achieve accuracies of up to 76% and compare them with other tools . the proposed algorithms are based on satirical news sources and fact-checking websites . |
Box of Lies: Multimodal Deception Detection in Dialogues (N19-1)
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| Challenge: | Deception occurs during everyday conversations, but this setting has received little attention from the research community. |
| Approach: | They propose to analyze multimodal deceptive dialogues in a box of lies game . they use facial and linguistic annotations to identify deceptives and truthful behaviors . |
| Outcome: | The proposed model outperforms both a random and a human baseline and achieves up to 69% accuracy in distinguishing deceptive and truthful behaviors. |