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An engineering view on emotions and speech: From analysis and predictive models to responsible human-centered applications
The substantial growth of Internet-of-Things technology and the ubiquity of smartphone
devices has increased the public and industry focus on speech emotion recognition (SER) …
devices has increased the public and industry focus on speech emotion recognition (SER) …
Minority views matter: Evaluating speech emotion classifiers with human subjective annotations by an all-inclusive aggregation rule
When selecting test data for subjective tasks, most studies define ground truth labels using
aggregation methods such as the majority or plurality rules. These methods discard data …
aggregation methods such as the majority or plurality rules. These methods discard data …
EMO-SUPERB: An in-depth look at speech emotion recognition
Speech emotion recognition (SER) is a pivotal technology for human-computer interaction
systems. However, 80.77% of SER papers yield results that cannot be reproduced. We …
systems. However, 80.77% of SER papers yield results that cannot be reproduced. We …
Open-Emotion: A Reproducible EMO-Superb For Speech Emotion Recognition Systems
Speech emotion recognition (SER) is an essential technology for human-computer
interaction systems. However, the previous study reveals that 80.77% of SER papers yield …
interaction systems. However, the previous study reveals that 80.77% of SER papers yield …
Estimating the uncertainty in emotion attributes using deep evidential regression
In automatic emotion recognition (AER), labels assigned by different human annotators to
the same utterance are often inconsistent due to the inherent complexity of emotion and the …
the same utterance are often inconsistent due to the inherent complexity of emotion and the …
Exploiting co-occurrence frequency of emotions in perceptual evaluations to train a speech emotion classifier
Previous studies on speech emotion recognition (SER) with categorical emotions have often
formulated the task as a single-label classification problem, where the emotions are …
formulated the task as a single-label classification problem, where the emotions are …
A Primary task driven adaptive loss function for multi-task speech emotion recognition
LY Liu, WZ Liu, L Feng - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Abstract Although Speech Emotion Recognition (SER) is becoming an active research area,
the state-of-the-art performance is limited by the scarcity of emotional datasets. The …
the state-of-the-art performance is limited by the scarcity of emotional datasets. The …
Personality-assisted mood modeling with historical reviews for sentiment classification
Review sentiment classification aims to predict user sentiment for given user-generated
review. Most of the existing methods enhance their sentiment classifiers by incorporating …
review. Most of the existing methods enhance their sentiment classifiers by incorporating …
Deep temporal clustering features for speech emotion recognition
Deep clustering is a popular unsupervised technique for feature representation learning. We
recently proposed the chunk-based DeepEmoCluster framework for speech emotion …
recently proposed the chunk-based DeepEmoCluster framework for speech emotion …
Learning with rater-expanded label space to improve speech emotion recognition
Automatic sensing of emotional information in speech is important for numerous everyday
applications. Conventional Speech Emotion Recognition (SER) models rely on averaging or …
applications. Conventional Speech Emotion Recognition (SER) models rely on averaging or …