activity
20182022
most citedUnsupervised low-rank representations for speech emotion recognition

12 citations · 30 across the 7 of their papers we have counts for

collaborators

13 papers

cs.CL2022

Adapted Multimodal BERT with Layer-wise Fusion for Sentiment Analysis

Odysseas S. Chlapanis, Georgios Paraskevopoulos, Alexandros Potamianos

Multimodal learning pipelines have benefited from the success of pretrained language models. However, this comes at the cost of increased model parameters. In this work, we propose…

cs.CV20222 cited

Extending Compositional Attention Networks for Social Reasoning in Videos

Christina Sartzetaki, Georgios Paraskevopoulos, Alexandros Potamianos

We propose a novel deep architecture for the task of reasoning about social interactions in videos. We leverage the multi-step reasoning capabilities of Compositional Attention Net…

cs.LG20222 cited

MMLatch: Bottom-up Top-down Fusion for Multimodal Sentiment Analysis

Georgios Paraskevopoulos, Efthymios Georgiou, Alexandros Potamianos

Current deep learning approaches for multimodal fusion rely on bottom-up fusion of high and mid-level latent modality representations (late/mid fusion) or low level sensory inputs…

cs.CL20211 cited

EmpBot: A T5-based Empathetic Chatbot focusing on Sentiments

Emmanouil Zaranis, Georgios Paraskevopoulos, Athanasios Katsamanis +1

In this paper, we introduce EmpBot: an end-to-end empathetic chatbot. Empathetic conversational agents should not only understand what is being discussed, but also acknowledge the…

cs.CL2021

UDALM: Unsupervised Domain Adaptation through Language Modeling

Constantinos Karouzos, Georgios Paraskevopoulos, Alexandros Potamianos

In this work we explore Unsupervised Domain Adaptation (UDA) of pretrained language models for downstream tasks. We introduce UDALM, a fine-tuning procedure, using a mixed classifi…

cs.LG202112 cited

Unsupervised low-rank representations for speech emotion recognition

Georgios Paraskevopoulos, Efthymios Tzinis, Nikolaos Ellinas +2

We examine the use of linear and non-linear dimensionality reduction algorithms for extracting low-rank feature representations for speech emotion recognition. Two feature sets are…