Speech emotion recognition with co-attention based multi-level acoustic information
Speech Emotion Recognition (SER) aims to help the machine to understand human's
subjective emotion from only audio in-formation. However, extracting and utilizing …
subjective emotion from only audio in-formation. However, extracting and utilizing …
Efficient multimodal transformer with dual-level feature restoration for robust multimodal sentiment analysis
With the proliferation of user-generated online videos, Multimodal Sentiment Analysis (MSA)
has attracted increasing attention recently. Despite significant progress, there are still two …
has attracted increasing attention recently. Despite significant progress, there are still two …
Contextual and cross-modal interaction for multi-modal speech emotion recognition
Speech emotion recognition combining linguistic content and audio signals in the dialog is a
challenging task. Nevertheless, previous approaches have failed to explore emotion cues in …
challenging task. Nevertheless, previous approaches have failed to explore emotion cues in …
Multimodal fusion on low-quality data: A comprehensive survey
Multimodal fusion focuses on integrating information from multiple modalities with the goal of
more accurate prediction, which has achieved remarkable progress in a wide range of …
more accurate prediction, which has achieved remarkable progress in a wide range of …
Multimodal emotion recognition using cross modal audio-video fusion with attention and deep metric learning
In the last few years, the multi-modal emotion recognition has become an important research
issue in the affective computing community due to its wide range of applications that include …
issue in the affective computing community due to its wide range of applications that include …
Attention-based multi-learning approach for speech emotion recognition with dilated convolution
The success of deep learning in speech emotion recognition has led to its application in
resource-constrained devices. It has been applied in human-to-machine interaction …
resource-constrained devices. It has been applied in human-to-machine interaction …
Is cross-attention preferable to self-attention for multi-modal emotion recognition?
Humans express their emotions via facial expressions, voice intonation and word choices.
To infer the nature of the underlying emotion, recognition models may use a single modality …
To infer the nature of the underlying emotion, recognition models may use a single modality …
AMPS: Predicting popularity of short-form videos using multi-modal attention mechanisms in social media marketing environments
Emerging as a dominant content format amid the shift from television to mobile, short-form
videos wield immense potential across diverse domains. However, the scarcity of datasets …
videos wield immense potential across diverse domains. However, the scarcity of datasets …
A cross-modal fusion network based on self-attention and residual structure for multimodal emotion recognition
The audio-video based multimodal emotion recognition has attracted a lot of attention due to
its robust performance. Most of the existing methods focus on proposing different cross …
its robust performance. Most of the existing methods focus on proposing different cross …