Search Results for author:
Found 9 papers, 1 papers with code
Multimodal Contextual Dialogue Breakdown Detection for Conversational AI Models
Detecting dialogue breakdown in real time is critical for conversational AI systems, because it enables taking corrective action to successfully complete a task.
Graph Integrated Language Transformers for Next Action Prediction in Complex Phone Calls
Current Conversational AI systems employ different machine learning pipelines, as well as external knowledge sources and business logic to predict the next action.
Discourse Relation Embeddings: Representing the Relations between Discourse Segments in Social Media
Discourse relations are typically modeled as a discrete class that characterizes the relation between segments of text (e. g. causal explanations, expansions).
World Trade Center responders in their own words: Predicting PTSD symptom trajectories with AI-based language analyses of interviews
This study sought to test the ability of AI-based language assessments to predict PTSD symptom trajectories among responders.
Author's Sentiment Prediction
We introduce PerSenT, a dataset of crowd-sourced annotations of the sentiment expressed by the authors towards the main entities in news articles.
Suicide Risk Assessment with Multi-level Dual-Context Language and BERT
Mental health predictive systems typically model language as if from a single context (e. g. Twitter posts, status updates, or forum posts) and often limited to a single level of analysis (e. g. either the message-level or user-level).
Causal Explanation Analysis on Social Media
Understanding causal explanations - reasons given for happenings in one's life - has been found to be an important psychological factor linked to physical and mental health.
Human Centered NLP with User-Factor Adaptation
We pose the general task of user-factor adaptation {--} adapting supervised learning models to real-valued user factors inferred from a background of their language, reflecting the idea that a piece of text should be understood within the context of the user that wrote it.
