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Found 42 papers, 3 papers with code
CHoRaL: Collecting Humor Reaction Labels from Millions of Social Media Users
Humor detection has gained attention in recent years due to the desire to understand user-generated content with figurative language.
Automatic Detection and Prediction of Psychiatric Hospitalizations From Social Media Posts
We address the problem of predicting psychiatric hospitalizations using linguistic features drawn from social media posts.
Detection of Mental Health from Reddit via Deep Contextualized Representations
We address the problem of automatic detection of psychiatric disorders from the linguistic content of social media posts.
A Novel Methodology for Developing Automatic Harassment Classifiers for Twitter
Most efforts at identifying abusive speech online rely on public corpora that have been scraped from websites using keyword-based queries or released by site or platform owners for research purposes.
Using Adaptive Empathetic Responses for Teaching English
Existing English-teaching chatbots rarely incorporate empathy explicitly in their feedback, but empathetic feedback could help keep students engaged and reduce learner anxiety.
QASE Enhanced PLMs: Improved Control in Text Generation for MRC
To address the challenges of out-of-control generation in generative models for machine reading comprehension (MRC), we introduce the Question-Attended Span Extraction (QASE) module.
Measuring Entrainment in Spontaneous Code-switched Speech
It is well-known that speakers who entrain to one another have more successful conversations than those who do not.
Noise robust speech emotion recognition with signal-to-noise ratio adapting speech enhancement
Speech emotion recognition (SER) often experiences reduced performance due to background noise.
MultiPA: a multi-task speech pronunciation assessment system for a closed and open response scenario
The design of automatic speech pronunciation assessment can be categorized into closed and open response scenarios, each with strengths and limitations.
Multi-Modality Multi-Loss Fusion Network
In this work we investigate the optimal selection and fusion of features across multiple modalities and combine these in a neural network to improve emotion detection.
Ranked #1 on
Multimodal Sentiment Analysis
on CH-SIMS
DialGuide: Aligning Dialogue Model Behavior with Developer Guidelines
These guidelines provide information about the context they are applicable to and what should be included in the response, allowing the models to generate responses that are more closely aligned with the developer's expectations and intent.
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence
In September 2016, Stanford's "One Hundred Year Study on Artificial Intelligence" project (AI100) issued the first report of its planned long-term periodic assessment of artificial intelligence (AI) and its impact on society.
A Survey on Open Information Extraction from Rule-based Model to Large Language Model (meta)
Open Information Extraction (OpenIE) represents a crucial NLP task aimed at deriving structured information from unstructured text, unrestricted by relation type or domain.
Understanding How People Rate Their Conversations
In this work, we conduct a study to better understand how people rate their interactions with conversational agents.
``Talk to me with left, right, and angles'': Lexical entrainment in spoken Hebrew dialogue
It has been well-documented for several languages that human interlocutors tend to adapt their linguistic productions to become more similar to each other.
Acoustic-Prosodic and Lexical Cues to Deception and Trust: Deciphering How People Detect Lies
We analyzed the acoustic-prosodic and linguistic characteristics of language trusted and mistrusted by raters and compared these to characteristics of actual truthful and deceptive language to understand how perception aligns with reality.
Part of speech tagging for code switched data
We address the problem of Part of Speech tagging (POS) in the context of linguistic code switching (CS).
Crowdsourced Hedge Term Disambiguation
We address the issue of acquiring quality annotations of hedging words and phrases, linguistic phenomenona in which words, sounds, or other constructions are used to express ambiguity or uncertainty.
Named Entity Recognition on Code-Switched Data: Overview of the CALCS 2018 Shared Task
In the third shared task of the Computational Approaches to Linguistic Code-Switching (CALCS) workshop, we focus on Named Entity Recognition (NER) on code-switched social-media data.
SpatialNet: A Declarative Resource for Spatial Relations
This paper introduces SpatialNet, a novel resource which links linguistic expressions to actual spatial configurations.
Joint Part-of-Speech and Language ID Tagging for Code-Switched Data
Code-switching is the fluent alternation between two or more languages in conversation between bilinguals.
Using Hedge Detection to Improve Committed Belief Tagging
We describe a novel method for identifying hedge terms using a set of manually constructed rules.
Linguistic Cues to Deception and Perceived Deception in Interview Dialogues
We explore deception detection in interview dialogues.
Comparing Approaches for Automatic Question Identification
Collecting spontaneous speech corpora that are open-ended, yet topically constrained, is increasingly popular for research in spoken dialogue systems and speaker state, inter alia.
Crowdsourcing Universal Part-Of-Speech Tags for Code-Switching
We split the annotation task into three subtasks: one in which a subset of tokens are labeled automatically, one in which questions are specifically designed to disambiguate a subset of high frequency words, and a more general cascaded approach for the remaining data in which questions are displayed to the worker following a decision tree structure.
Incrementally Learning a Dependency Parser to Support Language Documentation in Field Linguistics
We have created a new parallel corpus of descriptions of spatial relations and motion events, based on pictures and video clips used by field linguists for elicitation of language from native speaker informants.
Teenage and adult speech in school context: building and processing a corpus of European Portuguese
We present a corpus of European Portuguese spoken by teenagers and adults in school context, CPE-FACES, with an overview of the differential characteristics of high school oral presentations and the challenges this data poses to automatic speech processing.
