278 citations · 447 across the 23 of their papers we have counts for
25 papers
Comparative Analysis of Personalized Voice Activity Detection Systems: Assessing Real-World Effectiveness
Satyam Kumar, Sai Srujana Buddi, Utkarsh Oggy Sarawgi +6
Voice activity detection (VAD) is a critical component in various applications such as speech recognition, speech enhancement, and hands-free communication systems. With the increa…
Device-Directed Speech Detection: Regularization via Distillation for Weakly-Supervised Models
Vineet Garg, Ognjen Rudovic, Pranay Dighe +5
We address the problem of detecting speech directed to a device that does not contain a specific wake-word. Specifically, we focus on audio coming from a touch-based invocation. Mi…
Streaming on-device detection of device directed speech from voice and touch-based invocation
Ognjen Rudovic, Akanksha Bindal, Vineet Garg +3
When interacting with smart devices such as mobile phones or wearables, the user typically invokes a virtual assistant (VA) by saying a keyword or by pressing a button on the devic…
DeepFN: Towards Generalizable Facial Action Unit Recognition with Deep Face Normalization
Javier Hernandez, Daniel McDuff, Ognjen +3
Facial action unit recognition has many applications from market research to psychotherapy and from image captioning to entertainment. Despite its recent progress, deployment of th…
Toward Personalized Affect-Aware Socially Assistive Robot Tutors in Long-Term Interventions for Children with Autism
Zhonghao Shi, Thomas R Groechel, Shomik Jain +3
Affect-aware socially assistive robotics (SAR) has shown great potential for augmenting interventions for children with autism spectrum disorders (ASD). However, current SAR cannot…
Personalized Federated Deep Learning for Pain Estimation From Face Images
Ognjen Rudovic, Nicolas Tobis, Sebastian Kaltwang +4
Standard machine learning approaches require centralizing the users' data in one computer or a shared database, which raises data privacy and confidentiality concerns. Therefore, l…
Fast and Effective Adaptation of Facial Action Unit Detection Deep Model
Mihee Lee, Ognjen Rudovic, Vladimir Pavlovic +1
Detecting facial action units (AU) is one of the fundamental steps in automatic recognition of facial expression of emotions and cognitive states. Though there have been a variety…
Multi-modal Active Learning From Human Data: A Deep Reinforcement Learning Approach
Ognjen Rudovic, Meiru Zhang, Bjorn Schuller +1
Human behavior expression and experience are inherently multi-modal, and characterized by vast individual and contextual heterogeneity. To achieve meaningful human-computer and hum…
Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes
Ognjen Rudovic, Yuria Utsumi, Ricardo Guerrero +3
We introduce a novel personalized Gaussian Process Experts (pGPE) model for predicting per-subject ADAS-Cog13 cognitive scores -- a significant predictor of Alzheimer's Disease (AD…
Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach
Behnam Gholami, Pritish Sahu, Ognjen Rudovic +2
Unsupervised domain adaptation (uDA) models focus on pairwise adaptation settings where there is a single, labeled, source and a single target domain. However, in many real-world s…
RoboChain: A Secure Data-Sharing Framework for Human-Robot Interaction
Eduardo Castelló Ferrer, Ognjen Rudovic, Thomas Hardjono +1
Robots have potential to revolutionize the way we interact with the world around us. One of their largest potentials is in the domain of mobile health where they can be used to fac…
Multi-Instance Dynamic Ordinal Random Fields for Weakly-supervised Facial Behavior Analysis
Adria Ruiz, Ognjen Rudovic, Xavier Binefa +1
We propose a Multi-Instance-Learning (MIL) approach for weakly-supervised learning problems, where a training set is formed by bags (sets of feature vectors or instances) and only…
Personalized Gaussian Processes for Forecasting of Alzheimer's Disease Assessment Scale-Cognition Sub-Scale (ADAS-Cog13)
Yuria Utsumi, Ognjen Rudovic, Kelly Peterson +2
In this paper, we introduce the use of a personalized Gaussian Process model (pGP) to predict per-patient changes in ADAS-Cog13 -- a significant predictor of Alzheimer's Disease (A…
Personalized Machine Learning for Robot Perception of Affect and Engagement in Autism Therapy
Ognjen Rudovic, Jaeryoung Lee, Miles Dai +2
Robots have great potential to facilitate future therapies for children on the autism spectrum. However, existing robots lack the ability to automatically perceive and respond to h…
Personalized Gaussian Processes for Future Prediction of Alzheimer's Disease Progression
Kelly Peterson, Ognjen Rudovic, Ricardo Guerrero +1
In this paper, we introduce the use of a personalized Gaussian Process model (pGP) to predict the key metrics of Alzheimer's Disease progression (MMSE, ADAS-Cog13, CDRSB and CS) ba…
Physiological and behavioral profiling for nociceptive pain estimation using personalized multitask learning
Daniel Lopez-Martinez, Ognjen Rudovic, Rosalind Picard
Pain is a subjective experience commonly measured through patient's self report. While there exist numerous situations in which automatic pain estimation methods may be preferred,…
Unsupervised Domain Adaptation with Copula Models
Cuong D. Tran, Ognjen Rudovic, Vladimir Pavlovic
We study the task of unsupervised domain adaptation, where no labeled data from the target domain is provided during training time. To deal with the potential discrepancy between t…
DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain
Dianbo Liu, Fengjiao Peng, Andrew Shea +3
Previous research on automatic pain estimation from facial expressions has focused primarily on "one-size-fits-all" metrics (such as PSPI). In this work, we focus on directly estim…
Personalized Automatic Estimation of Self-reported Pain Intensity from Facial Expressions
Daniel Lopez Martinez, Ognjen Rudovic, Rosalind Picard
Pain is a personal, subjective experience that is commonly evaluated through visual analog scales (VAS). While this is often convenient and useful, automatic pain detection systems…
DeepCoder: Semi-parametric Variational Autoencoders for Automatic Facial Action Coding
Dieu Linh Tran, Robert Walecki, Ognjen Rudovic +3
Human face exhibits an inherent hierarchy in its representations (i.e., holistic facial expressions can be encoded via a set of facial action units (AUs) and their intensity). Vari…
Multi-instance Dynamic Ordinal Random Fields for Weakly-Supervised Pain Intensity Estimation
Adria Ruiz, Ognjen Rudovic, Xavier Binefa +1
In this paper, we address the Multi-Instance-Learning (MIL) problem when bag labels are naturally represented as ordinal variables (Multi--Instance--Ordinal Regression). Moreover,…
Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units
Stefanos Eleftheriadis, Ognjen Rudovic, Marc P. Deisenroth +1
We address the task of simultaneous feature fusion and modeling of discrete ordinal outputs. We propose a novel Gaussian process(GP) auto-encoder modeling approach. In particular,…
Gaussian Process Domain Experts for Model Adaptation in Facial Behavior Analysis
Stefanos Eleftheriadis, Ognjen Rudovic, Marc P. Deisenroth +1
We present a novel approach for supervised domain adaptation that is based upon the probabilistic framework of Gaussian processes (GPs). Specifically, we introduce domain-specific…
Variable-state Latent Conditional Random Fields for Facial Expression Recognition and Action Unit Detection
Robert Walecki, Ognjen Rudovic, Vladimir Pavlovic +1
Automated recognition of facial expressions of emotions, and detection of facial action units (AUs), from videos depends critically on modeling of their dynamics. These dynamics ar…