A deep neural network based multi-task learning approach to hate speech detection
With the advent of the internet and numerous social media platforms, citizens now have
enormous opportunities to express and share their opinions on various societal and political …
enormous opportunities to express and share their opinions on various societal and political …
Multimodal approach of speech emotion recognition using multi-level multi-head fusion attention-based recurrent neural network
Speech emotion recognition is a challenging but important task in human computer
interaction (HCI). As technology and understanding of emotion are progressing, it is …
interaction (HCI). As technology and understanding of emotion are progressing, it is …
An emoji-aware multitask framework for multimodal sarcasm detection
Sarcasm is a case of implicit emotion and needs additional information like context and
multimodality for better detection. But sometimes, this additional information also fails to help …
multimodality for better detection. But sometimes, this additional information also fails to help …
Evaluating significant features in context‐aware multimodal emotion recognition with XAI methods
Expert systems are being extensively used to make critical decisions involving emotional
analysis in affective computing. The evolution of deep learning algorithms has improved the …
analysis in affective computing. The evolution of deep learning algorithms has improved the …
I didn't mean what I wrote! Exploring Multimodality for Sarcasm Detection
Sarcasm detection is, inherently, a non-trivial problem where people express negative
sentiment using positive insinuation words. Traditional approaches, in general, rely on the …
sentiment using positive insinuation words. Traditional approaches, in general, rely on the …
Multi-corpus learning for audio–visual emotions and sentiment recognition
Recognition of emotions and sentiment (affective states) from human audio–visual
information is widely used in healthcare, education, entertainment, and other fields; …
information is widely used in healthcare, education, entertainment, and other fields; …
RobinNet: A multimodal speech emotion recognition system with speaker recognition for social interactions
Y Khurana, S Gupta, R Sathyaraj… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
It is essential to understand the underlying emotions that are imparted through speech in
order to study social communications as well as to generate seamless human–computer …
order to study social communications as well as to generate seamless human–computer …
Task-specific speech enhancement and data augmentation for improved multimodal emotion recognition under noisy conditions
S Kshirsagar, A Pendyala, TH Falk - Frontiers in Computer Science, 2023 - frontiersin.org
Automatic emotion recognition (AER) systems are burgeoning and systems based on either
audio, video, text, or physiological signals have emerged. Multimodal systems, in turn, have …
audio, video, text, or physiological signals have emerged. Multimodal systems, in turn, have …
[PDF][PDF] A multi-level circulant cross-modal transformer for multimodal speech emotion recognition.
P Gong, J Liu, Z Wu, B Han… - … , Materials & Continua, 2023 - cdn.techscience.cn
Speech emotion recognition, as an important component of humancomputer interaction
technology, has received increasing attention. Recent studies have treated emotion …
technology, has received increasing attention. Recent studies have treated emotion …
An efficient fusion mechanism for multimodal low-resource setting
The effective fusion of multiple modalities (ie, text, acoustic, and visual) is a non-trivial task,
as these modalities often carry specific and diverse information and do not contribute …
as these modalities often carry specific and diverse information and do not contribute …