Search Results for author: Rosalind Picard

Found 23 papers, 6 papers with code

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.

Mixed Effects Random Forests for Personalised Predictions of Clinical Depression Severity

no code implementations24 Jan 2023 Robert A. Lewis, Asma Ghandeharioun, Szymon Fedor, Paola Pedrelli, Rosalind Picard, David Mischoulon

We suggest that this improved performance results from the ability of the mixed effects random forest to personalise model parameters to individuals in the dataset.

Computational Empathy Counteracts the Negative Effects of Anger on Creative Problem Solving

1 code implementation15 Aug 2022 Matthew Groh, Craig Ferguson, Robert Lewis, Rosalind Picard

In an online experiment with 1, 006 participants randomly assigned to an emotion elicitation intervention (with a control elicitation condition and anger elicitation condition) and a computational empathy intervention (with a control virtual agent and an empathic virtual agent), we examine how anger and empathy influence participants' performance in solving a word game based on Wordle.

Human Detection of Political Speech Deepfakes across Transcripts, Audio, and Video

no code implementations25 Feb 2022 Matthew Groh, Aruna Sankaranarayanan, Nikhil Singh, Dong Young Kim, Andrew Lippman, Rosalind Picard

Recent advances in technology for hyper-realistic visual and audio effects provoke the concern that deepfake videos of political speeches will soon be indistinguishable from authentic video recordings.

Face Swapping Human Detection +1

Deepfake Detection by Human Crowds, Machines, and Machine-informed Crowds

1 code implementation13 May 2021 Matthew Groh, Ziv Epstein, Chaz Firestone, Rosalind Picard

The recent emergence of machine-manipulated media raises an important societal question: how can we know if a video that we watch is real or fake?

DeepFake Detection Face Swapping

Human-centric Dialog Training via Offline Reinforcement Learning

1 code implementation EMNLP 2020 Natasha Jaques, Judy Hanwen Shen, Asma Ghandeharioun, Craig Ferguson, Agata Lapedriza, Noah Jones, Shixiang Shane Gu, Rosalind Picard

We start by hosting models online, and gather human feedback from real-time, open-ended conversations, which we then use to train and improve the models using offline reinforcement learning (RL).

Language Modelling Offline RL +2

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.

Way Off-Policy Batch Deep Reinforcement Learning of Human Preferences in Dialog

no code implementations ICLR 2020 Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen, Craig Ferguson, Agata Lapedriza, Noah Jones, Shixiang Gu, Rosalind Picard

This is a critical shortcoming for applying RL to real-world problems where collecting data is expensive, and models must be tested offline before being deployed to interact with the environment -- e. g. systems that learn from human interaction.

OpenAI Gym Open-Domain Dialog +3

Hierarchical Reinforcement Learning for Open-Domain Dialog

1 code implementation17 Sep 2019 Abdelrhman Saleh, Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen, Rosalind Picard

Open-domain dialog generation is a challenging problem; maximum likelihood training can lead to repetitive outputs, models have difficulty tracking long-term conversational goals, and training on standard movie or online datasets may lead to the generation of inappropriate, biased, or offensive text.

Hierarchical Reinforcement Learning Open-Domain Dialog +2

Detection of Real-world Driving-induced Affective State Using Physiological Signals and Multi-view Multi-task Machine Learning

no code implementations19 Jul 2019 Daniel Lopez-Martinez, Neska El-Haouij, Rosalind Picard

This may lead to empathic automotive user interfaces that account for the driver's emotional state and influence the driver in order to improve safety.

Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog

1 code implementation30 Jun 2019 Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen, Craig Ferguson, Agata Lapedriza, Noah Jones, Shixiang Gu, Rosalind Picard

Most deep reinforcement learning (RL) systems are not able to learn effectively from off-policy data, especially if they cannot explore online in the environment.

Open-Domain Dialog Q-Learning +2

Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems

2 code implementations NeurIPS 2019 Asma Ghandeharioun, Judy Hanwen Shen, Natasha Jaques, Craig Ferguson, Noah Jones, Agata Lapedriza, Rosalind Picard

To investigate the strengths of this novel metric and interactive evaluation in comparison to state-of-the-art metrics and human evaluation of static conversations, we perform extended experiments with a set of models, including several that make novel improvements to recent hierarchical dialog generation architectures through sentiment and semantic knowledge distillation on the utterance level.

Dialogue Evaluation Knowledge Distillation

Deep Reinforcement Learning for Optimal Critical Care Pain Management with Morphine using Dueling Double-Deep Q Networks

no code implementations25 Apr 2019 Daniel Lopez-Martinez, Patrick Eschenfeldt, Sassan Ostvar, Myles Ingram, Chin Hur, Rosalind Picard

Our results demonstrate that reinforcement learning may be used to aid decision making in the intensive care setting by providing personalized pain management interventions.

Decision Making Management +2

Learning via social awareness: Improving a deep generative sketching model with facial feedback

no code implementations13 Feb 2018 Natasha Jaques, Jennifer McCleary, Jesse Engel, David Ha, Fred Bertsch, Rosalind Picard, Douglas Eck

We use a Latent Constraints GAN (LC-GAN) to learn from the facial feedback of a small group of viewers, by optimizing the model to produce sketches that it predicts will lead to more positive facial expressions.

Personalized Machine Learning for Robot Perception of Affect and Engagement in Autism Therapy

no code implementations4 Feb 2018 Ognjen Rudovic, Jaeryoung Lee, Miles Dai, Bjorn Schuller, Rosalind Picard

To tackle the heterogeneity in behavioral cues of children with autism, we use the latest advances in deep learning to formulate a personalized machine learning (ML) framework for automatic perception of the childrens affective states and engagement during robot-assisted autism therapy.

BIG-bench Machine Learning

DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain

no code implementations9 Aug 2017 Dianbo Liu, Fengjiao Peng, Andrew Shea, Ognjen, Rudovic, Rosalind Picard

Previous research on automatic pain estimation from facial expressions has focused primarily on "one-size-fits-all" metrics (such as PSPI).

Multi-Task Learning

Personalized Automatic Estimation of Self-reported Pain Intensity from Facial Expressions

no code implementations22 Jun 2017 Daniel Lopez Martinez, Ognjen Rudovic, Rosalind Picard

To the best of our knowledge, this is the first approach to automatically estimate VAS from face images.

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