Domain adaptation: challenges, methods, datasets, and applications
Deep Neural Networks (DNNs) trained on one dataset (source domain) do not perform well
on another set of data (target domain), which is different but has similar properties as the …
on another set of data (target domain), which is different but has similar properties as the …
Toward Label-Efficient Emotion and Sentiment Analysis This article introduces label-efficient emotion and sentiment analysis from the computational perspective …
Emotion and sentiment play a central role in various human activities, such as perception,
decision-making, social interaction, and logical reasoning. Developing artificial emotional …
decision-making, social interaction, and logical reasoning. Developing artificial emotional …
[PDF][PDF] SOT: Self-supervised Learning-Assisted Optimal Transport for Unsupervised Adaptive Speech Emotion Recognition
In cross-domain speech emotion recognition (SER), reducing the global probability
distribution distance (GPDD) between different domains plays a crucial role in unsupervised …
distribution distance (GPDD) between different domains plays a crucial role in unsupervised …
[PDF][PDF] Toward Label-Efficient Emotion and Sentiment Analysis.
Emotion and sentiment play a central role in various human activities, such as perception,
decision-making, social interaction, and logical reasoning. Developing artificial emotional …
decision-making, social interaction, and logical reasoning. Developing artificial emotional …
Self-Supervised Domain Exploration with an Optimal Transport Regularization for Open Set Cross-Domain Speech Emotion Recognition
In the tasks of domain adaptation (DA) for speech emotion recognition (SER), self-
supervised learning (SSL) algorithms could effectively explore domain and structural …
supervised learning (SSL) algorithms could effectively explore domain and structural …
Multimodal Transfer Learning for Oral Presentation Assessment
Oral communication has consistently been ranked as a key skill, with 90 percent of hiring
managers and 80 percent of business executives saying it is very important for college …
managers and 80 percent of business executives saying it is very important for college …
Improving speech emotion recognition with data expression aware multi-task learning
Majority of speech emotion recognition (SER) systems are developed using databases with
simulating speech performed by professional actors. Whereas, concerning real-world …
simulating speech performed by professional actors. Whereas, concerning real-world …
Elicitation-Based Curriculum Learning for Improving Speech Emotion Recognition
Speech emotion recognition (SER) is an essential component of human-computer
interaction systems, enabling machines to understand and respond to human emotions. To …
interaction systems, enabling machines to understand and respond to human emotions. To …
Classifying Emotions Across Variations in Speech Data
A Keesing - 2023 - researchspace.auckland.ac.nz
As speech-enabled technology becomes more prevalent, computers need to predict human
emotions accurately. Speech emotion recognition (SER) predicts emotions using just …
emotions accurately. Speech emotion recognition (SER) predicts emotions using just …