AIConfPaper
← Search

Panayiotis G. Georgiou

12 accepted papers

2024

A Multimodal Approach to Device-Directed Speech Detection with Large Language Models

Dominik Wagner, Alexander W. Churchill, Siddharth Sigtia, Panayiotis G. Georgiou, Matt Mirsamadi, Aarshee Mishra +1
ICASSP 2024accepted

Interactions with virtual assistants typically start with a predefined trigger phrase followed by the user command. To make interactions with the assistant more intuitive, we explore whether it is feasible to drop the requirement that users must begin each command with a trigger phrase. We explore t…

Cited by 0Source ↗Scholar ↗
2020

Automatic Prediction of Suicidal Risk in Military Couples Using Multimodal Interaction Cues from Couples Conversations

Sandeep Nallan Chakravarthula, Md. Nasir, Shao-Yen Tseng, Haoqi Li, Tae Jin Park, Brian R. Baucom +3
ICASSP 2020accepted

Suicide is a major societal challenge globally, with a wide range of risk factors, from individual health, psychological and behavioral elements to socio-economic aspects. Military personnel, in particular, are at especially high risk. Crisis resources, while helpful, are often constrained by access…

Cited by 0Source ↗Scholar ↗
2020

Speaker-Invariant Affective Representation Learning via Adversarial Training

Haoqi Li, Ming Tu, Jing Huang, Shrikanth Narayanan, Panayiotis G. Georgiou
ICASSP 2020accepted

Representation learning for speech emotion recognition is challenging due to labeled data sparsity issue and lack of gold-standard references. In addition, there is much variability from input speech signals, human subjective perception of the signals and emotion label ambiguity. In this paper, we p…

Cited by 0Source ↗Scholar ↗
2019

Hierarchy-aware Loss Function on a Tree Structured Label Space for Audio Event Detection

Arindam Jati, Naveen Kumar, Ruxin Chen, Panayiotis G. Georgiou
ICASSP 2019accepted

The paper introduces a hierarchy-aware loss function in a Deep Neural Network for an audio event detection task that has a bi-level tree structured label space. The goal is not only to improve audio event detection performance at all levels in the label hierarchy, but also to produce better audio em…

Cited by 0Source ↗Scholar ↗
2019

Improving the Prediction of Therapist Behaviors in Addiction Counseling by Exploiting Class Confusions

Zhuohao Chen, Karan Singla, James Gibson, Dogan Can, Zac E. Imel, David C. Atkins +2
ICASSP 2019accepted

In this work we address the problem of joint prosodic and lexical behavioral annotation for addiction counseling. We expand on past work that employed Recurrent Neural Networks (RNNs) on multimodal features by grouping and classifying subsets of classes. We propose two implementations: One is hierar…

Cited by 0Source ↗Scholar ↗
2019

Role Specific Lattice Rescoring for Speaker Role Recognition from Speech Recognition Outputs

Nikolaos Flemotomos, Panayiotis G. Georgiou, David C. Atkins, Shrikanth S. Narayanan
ICASSP 2019accepted

The language patterns followed by different speakers who play specific roles in conversational interactions provide valuable cues for the task of Speaker Role Recognition (SRR). Given the speech signal, existing algorithms typically try to find such patterns in the output of an Automatic Speech Reco…

Cited by 0Source ↗Scholar ↗
2018

A Deep Reinforcement Learning Framework for Identifying Funny Scenes in Movies

Haoqi Li, Naveen Kumar, Ruxin Chen, Panayiotis G. Georgiou
ICASSP 2018accepted

This paper presents a novel deep Reinforcement Learning (RL) framework for classifying movie scenes based on affect using the face images detected in the video stream as input. Extracting affective information from the video is a challenging task modulating complex visual and temporal representation…

Cited by 0Source ↗Scholar ↗
2018

Towards Predicting Physiology from Speech During Stressful Conversations: Heart Rate and Respiratory Sinus Arrhythmia

Arindam Jati, Paula G. Williams, Brian R. Baucom, Panayiotis G. Georgiou
ICASSP 2018accepted

Being affected by mental stress during conversations might have a direct or indirect effect on our speech acoustics as well as on our physiological responses. This paper presents a study on finding the relationship between these two modalities, speech acoustics and physiology, during stressful conve…

Cited by 0Source ↗Scholar ↗
2017

Unsupervised latent behavior manifold learning from acoustic features: Audio2behavior

Haoqi Li, Brian R. Baucom, Panayiotis G. Georgiou
ICASSP 2017accepted

Behavioral annotation using signal processing and machine learning is highly dependent on training data and manual annotations of behavioral labels. Previous studies have shown that speech information encodes significant behavioral information and be used in a variety of automated behavior recogniti…

Cited by 0Source ↗Scholar ↗
2015

A language-based generative model framework for behavioral analysis of couples' therapy

Sandeep Nallan Chakravarthula, Rahul Gupta, Brian R. Baucom, Panayiotis G. Georgiou
ICASSP 2015accepted

Observational studies for psychological evaluations rely on careful assessment of multiple behavioral cues. Recent studies have made good progress in automating the psychological evaluation, which often involved tedious manual annotation of a set of behavioral codes. However, the current methods imp…

Cited by 0Source ↗Scholar ↗
2015

Quantifying EDA synchrony through joint sparse representation: A case-study of couples' interactions

Theodora Chaspari, Brian R. Baucom, Adela C. Timmons, Andreas Tsiartas, Larissa Borofsky Del Piero, Katherine J. W. Baucom +3
ICASSP 2015accepted

The co-variation degree between individuals in their physiological signals can reveal insights about the quality of their interaction as well as their personal characteristics. In an effort to capture the amount of synchrony between Electrodermal Activity (EDA) streams occurring in parallel during d…

Cited by 0Source ↗Scholar ↗
2015

Redundancy analysis of behavioral coding for couples therapy and improved estimation of behavior from noisy annotations

Md. Nasir, Brian R. Baucom, Panayiotis G. Georgiou, Shrikanth S. Narayanan
ICASSP 2015accepted

Assessment and quantification of behavior is an important research objective in the recently developed field of behavioral signal processing. This paper focuses on the estimation of behavior from noisy human assessment. It aims to address the redundancy of behavioral descriptors for couples therapy…

Cited by 0Source ↗Scholar ↗