Search Results for author: Cynthia Breazeal

Found 17 papers, 1 papers with code

MRF-Chat: Improving Dialogue with Markov Random Fields

no code implementations EMNLP 2021 Ishaan Grover, Matthew Huggins, Cynthia Breazeal, Hae Won Park

Recent state-of-the-art approaches in open-domain dialogue include training end-to-end deep-learning models to learn various conversational features like emotional content of response, symbolic transitions of dialogue contexts in a knowledge graph and persona of the agent and the user, among others.


AI Audit: A Card Game to Reflect on Everyday AI Systems

no code implementations29 May 2023 Safinah Ali, Vishesh Kumar, Cynthia Breazeal

The game mechanics reward systems that are ethically developed or that take steps to mitigate potential harms.


Modeling Empathic Similarity in Personal Narratives

no code implementations23 May 2023 Jocelyn Shen, Maarten Sap, Pedro Colon-Hernandez, Hae Won Park, Cynthia Breazeal

The most meaningful connections between people are often fostered through expression of shared vulnerability and emotional experiences in personal narratives.

Retrieval Semantic Similarity +1

HIINT: Historical, Intra- and Inter- personal Dynamics Modeling with Cross-person Memory Transformer

no code implementations21 May 2023 Yubin Kim, Dong Won Lee, Paul Pu Liang, Sharifa Algohwinem, Cynthia Breazeal, Hae Won Park

Accurately modeling affect dynamics, which refers to the changes and fluctuations in emotions and affective displays during human conversations, is crucial for understanding human interactions.

Language Modelling

Multipar-T: Multiparty-Transformer for Capturing Contingent Behaviors in Group Conversations

no code implementations19 Apr 2023 Dong Won Lee, Yubin Kim, Rosalind Picard, Cynthia Breazeal, Hae Won Park

As we move closer to real-world AI systems, AI agents must be able to deal with multiparty (group) conversations.

Adversarial Transformer Language Models for Contextual Commonsense Inference

no code implementations10 Feb 2023 Pedro Colon-Hernandez, Henry Lieberman, Yida Xin, Claire Yin, Cynthia Breazeal, Peter Chin

Contextualized or discourse aware commonsense inference is the task of generating coherent commonsense assertions (i. e., facts) from a given story, and a particular sentence from that story.

Knowledge Graphs Language Modelling

Joint Engagement Classification using Video Augmentation Techniques for Multi-person Human-robot Interaction

no code implementations28 Dec 2022 Yubin Kim, Huili Chen, Sharifa Alghowinem, Cynthia Breazeal, Hae Won Park

This work serves as the first step toward fully unlocking the potential of end-to-end video understanding models pre-trained on large public datasets and augmented with data augmentation and visualization techniques for affect recognition in the multi-person human-robot interaction in the wild.

Data Augmentation Face Swapping +1

Build-a-Bot: Teaching Conversational AI Using a Transformer-Based Intent Recognition and Question Answering Architecture

no code implementations14 Dec 2022 Kate Pearce, Sharifa Alghowinem, Cynthia Breazeal

As such, we propose the development of an open-source tool (Build-a-Bot) for students and teachers to not only create their own transformer-based chatbots based on their own course material, but also learn the fundamentals of AI through the model creation process.

Chatbot Data Augmentation +3

B$^3$RTDP: A Belief Branch and Bound Real-Time Dynamic Programming Approach to Solving POMDPs

no code implementations22 Oct 2022 Sigurdur Orn Adalgeirsson, Cynthia Breazeal

Partially Observable Markov Decision Processes (POMDPs) offer a promising world representation for autonomous agents, as they can model both transitional and perceptual uncertainties.

Explainable AI for Suicide Risk Assessment Using Eye Activities and Head Gestures

no code implementations10 Jun 2022 Siyu Liu, Catherine Lu, Sharifa Alghowinem, Lea Gotoh, Cynthia Breazeal, Hae Won Park

The prevalence of suicide has been on the rise since the 20th century, causing severe emotional damage to individuals, families, and communities alike.

feature selection

Introducing Variational Autoencoders to High School Students

no code implementations13 Nov 2021 Zhuoyue Lyu, Safinah Ali, Cynthia Breazeal

Generative Artificial Intelligence (AI) models are a compelling way to introduce K-12 students to AI education using an artistic medium, and hence have drawn attention from K-12 AI educators.

Philosophy Vocal Bursts Intensity Prediction

RetroGAN: A Cyclic Post-Specialization System for Improving Out-of-Knowledge and Rare Word Representations

1 code implementation Findings (ACL) 2021 Pedro Colon-Hernandez, Yida Xin, Henry Lieberman, Catherine Havasi, Cynthia Breazeal, Peter Chin

Retrofitting is a technique used to move word vectors closer together or further apart in their space to reflect their relationships in a Knowledge Base (KB).

Word Similarity

Combining pre-trained language models and structured knowledge

no code implementations28 Jan 2021 Pedro Colon-Hernandez, Catherine Havasi, Jason Alonso, Matthew Huggins, Cynthia Breazeal

In recent years, transformer-based language models have achieved state of the art performance in various NLP benchmarks.

Knowledge Graphs

Migratable AI : Investigating users' affect on identity and information migration of a conversational AI agent

no code implementations22 Oct 2020 Ravi Tejwani, Boris Katz, Cynthia Breazeal

Conversational AI agents are becoming ubiquitous and provide assistance to us in our everyday activities.

Migratable AI: Personalizing Dialog Conversations with migration context

no code implementations22 Oct 2020 Ravi Tejwani, Boris Katz, Cynthia Breazeal

The migration of conversational AI agents across different embodiments in order to maintain the continuity of the task has been recently explored to further improve user experience.

Information Retrieval Retrieval

Dyadic Speech-based Affect Recognition using DAMI-P2C Parent-child Multimodal Interaction Dataset

no code implementations20 Aug 2020 Huili Chen, Yue Zhang, Felix Weninger, Rosalind Picard, Cynthia Breazeal, Hae Won Park

Automatic speech-based affect recognition of individuals in dyadic conversation is a challenging task, in part because of its heavy reliance on manual pre-processing.

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