Recent developments in MIR have led to several benchmark deep learning m...
In this paper, we study the problem of producing a comprehensive video
s...
Data augmentation is a prevalent technique for improving performance in
...
Automated audio captioning is multi-modal translation task that aim to
g...
We propose a deep architecture for depression detection from social medi...
Modern speech recognition systems exhibits rapid performance degradation...
Designing powerful adversarial attacks is of paramount importance for th...
Multimodal learning pipelines have benefited from the success of pretrai...
Studying under-represented music traditions under the MIR scope is cruci...
We propose a novel deep architecture for the task of reasoning about soc...
Task-oriented dialogue systems often employ a Dialogue State Tracker (DS...
Recent deep learning Text-to-Speech (TTS) systems have achieved impressi...
Current deep learning approaches for multimodal fusion rely on bottom-up...
In this paper, we introduce EmpBot: an end-to-end empathetic chatbot.
Em...
In this work we explore Unsupervised Domain Adaptation (UDA) of pretrain...
We examine the use of linear and non-linear dimensionality reduction
alg...
Contemporary state-of-the-art approaches to Zero-Shot Learning (ZSL) tra...
In this paper, we present a novel approach for incorporating external
kn...
In traditional Distributional Semantic Models (DSMs) the multiple senses...
Neural sequence-to-sequence models are currently the dominant approach i...
A growing number of state-of-the-art transfer learning methods employ
la...
We investigate the performance of features that can capture nonlinear
re...
In this paper we present our approach to tackle the Implicit Emotion Sha...
We present a novel view of nonlinear manifold learning using derivative-...
We present a novel view of nonlinear manifold learning using derivative-...
In this paper we present two deep-learning systems that competed at
SemE...
In this paper we present deep-learning models that submitted to the
SemE...
In this paper we present a deep-learning model that competed at SemEval-...
We introduce a tree-structured attention neural network for sentences an...