Search Results for author: Verónica Pérez-Rosas

Found 13 papers, 4 papers with code

Evaluating Automatic Speech Recognition Quality and Its Impact on Counselor Utterance Coding

no code implementations NAACL (CLPsych) 2021 Do June Min, Verónica Pérez-Rosas, Rada Mihalcea

Automatic speech recognition (ASR) is a crucial step in many natural language processing (NLP) applications, as often available data consists mainly of raw speech.

Automatic Speech Recognition speech-recognition

Counseling-Style Reflection Generation Using Generative Pretrained Transformers with Augmented Context

no code implementations SIGDIAL (ACL) 2020 Siqi Shen, Charles Welch, Rada Mihalcea, Verónica Pérez-Rosas

We introduce a counseling dialogue system that seeks to assist counselors while they are learning and refining their counseling skills.

Matching Tweets With Applicable Fact-Checks Across Languages

no code implementations14 Feb 2022 Ashkan Kazemi, Zehua Li, Verónica Pérez-Rosas, Scott A. Hale, Rada Mihalcea

We conduct both classification and retrieval experiments, in monolingual (English only), multilingual (Spanish, Portuguese), and cross-lingual (Hindi-English) settings using multilingual transformer models such as XLM-RoBERTa and multilingual embeddings such as LaBSE and SBERT.

Fact Checking

Extractive and Abstractive Explanations for Fact-Checking and Evaluation of News

no code implementations NAACL (NLP4IF) 2021 Ashkan Kazemi, Zehua Li, Verónica Pérez-Rosas, Rada Mihalcea

In this paper, we explore the construction of natural language explanations for news claims, with the goal of assisting fact-checking and news evaluation applications.

Fact Checking Language Modelling +1

Exploring the Value of Personalized Word Embeddings

no code implementations COLING 2020 Charles Welch, Jonathan K. Kummerfeld, Verónica Pérez-Rosas, Rada Mihalcea

Our results show that a subset of words belonging to specific psycholinguistic categories tend to vary more in their representations across users and that combining generic and personalized word embeddings yields the best performance, with a 4. 7% relative reduction in perplexity.

Language Modelling Word Embeddings

Biased TextRank: Unsupervised Graph-Based Content Extraction

no code implementations COLING 2020 Ashkan Kazemi, Verónica Pérez-Rosas, Rada Mihalcea

We introduce Biased TextRank, a graph-based content extraction method inspired by the popular TextRank algorithm that ranks text spans according to their importance for language processing tasks and according to their relevance to an input "focus."

Compositional Demographic Word Embeddings

1 code implementation EMNLP 2020 Charles Welch, Jonathan K. Kummerfeld, Verónica Pérez-Rosas, Rada Mihalcea

Word embeddings are usually derived from corpora containing text from many individuals, thus leading to general purpose representations rather than individually personalized representations.

Language Modelling Word Embeddings

Expressive Interviewing: A Conversational System for Coping with COVID-19

no code implementations EMNLP (NLP-COVID19) 2020 Charles Welch, Allison Lahnala, Verónica Pérez-Rosas, Siqi Shen, Sarah Seraj, Larry An, Kenneth Resnicow, James Pennebaker, Rada Mihalcea

The ongoing COVID-19 pandemic has raised concerns for many regarding personal and public health implications, financial security and economic stability.

Towards Automatic Detection of Misinformation in Online Medical Videos

no code implementations4 Sep 2019 Rui Hou, Verónica Pérez-Rosas, Stacy Loeb, Rada Mihalcea

Recent years have witnessed a significant increase in the online sharing of medical information, with videos representing a large fraction of such online sources.

Misinformation

Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)

1 code implementation5 Jun 2019 Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, Roger Zimmermann, Rada Mihalcea, Soujanya Poria

As a first step towards enabling the development of multimodal approaches for sarcasm detection, we propose a new sarcasm dataset, Multimodal Sarcasm Detection Dataset (MUStARD), compiled from popular TV shows.

Sarcasm Detection

Look Who's Talking: Inferring Speaker Attributes from Personal Longitudinal Dialog

1 code implementation25 Apr 2019 Charles Welch, Verónica Pérez-Rosas, Jonathan K. Kummerfeld, Rada Mihalcea

We examine a large dialog corpus obtained from the conversation history of a single individual with 104 conversation partners.

Automatic Detection of Fake News

no code implementations COLING 2018 Verónica Pérez-Rosas, Bennett Kleinberg, Alexandra Lefevre, Rada Mihalcea

The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content.

Fake News Detection

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