Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers
Speech is the most natural way of expressing ourselves as humans. It is only natural then to
extend this communication medium to computer applications. We define speech emotion …
extend this communication medium to computer applications. We define speech emotion …
Lipopolysaccharide-induced model of neuroinflammation: mechanisms of action, research application and future directions for its use
A Skrzypczak-Wiercioch, K Sałat - Molecules, 2022 - mdpi.com
Despite advances in antimicrobial and anti-inflammatory therapies, inflammation and its
consequences still remain a significant problem in medicine. Acute inflammatory responses …
consequences still remain a significant problem in medicine. Acute inflammatory responses …
Emotion recognition in speech using cross-modal transfer in the wild
Obtaining large, human labelled speech datasets to train models for emotion recognition is a
notoriously challenging task, hindered by annotation cost and label ambiguity. In this work …
notoriously challenging task, hindered by annotation cost and label ambiguity. In this work …
Cross corpus multi-lingual speech emotion recognition using ensemble learning
Receiving an accurate emotional response from robots has been a challenging task for
researchers for the past few years. With the advancements in technology, robots like service …
researchers for the past few years. With the advancements in technology, robots like service …
Categorical and dimensional affect analysis in continuous input: Current trends and future directions
H Gunes, B Schuller - Image and Vision Computing, 2013 - Elsevier
In the context of affective human behavior analysis, we use the term continuous input to refer
to naturalistic settings where explicit or implicit input from the subject is continuously …
to naturalistic settings where explicit or implicit input from the subject is continuously …
Domain adversarial for acoustic emotion recognition
M Abdelwahab, C Busso - IEEE/ACM Transactions on Audio …, 2018 - ieeexplore.ieee.org
The performance of speech emotion recognition is affected by the differences in data
distributions between train (source domain) and test (target domain) sets used to build and …
distributions between train (source domain) and test (target domain) sets used to build and …
Cross-corpus acoustic emotion recognition: Variances and strategies
As the recognition of emotion from speech has matured to a degree where it becomes
applicable in real-life settings, it is time for a realistic view on obtainable performances. Most …
applicable in real-life settings, it is time for a realistic view on obtainable performances. Most …
[PDF][PDF] Analysis of Deep Learning Architectures for Cross-Corpus Speech Emotion Recognition.
Abstract Speech Emotion Recognition (SER) is an important and challenging task for human-
computer interaction. In the literature deep learning architectures have been shown to yield …
computer interaction. In the literature deep learning architectures have been shown to yield …
Self supervised adversarial domain adaptation for cross-corpus and cross-language speech emotion recognition
Despite the recent advancement in speech emotion recognition (SER) within a single corpus
setting, the performance of these SER systems degrades significantly for cross-corpus and …
setting, the performance of these SER systems degrades significantly for cross-corpus and …
Emonet: A transfer learning framework for multi-corpus speech emotion recognition
In this manuscript, the topic of multi-corpus Speech Emotion Recognition (SER) is
approached from a deep transfer learning perspective. A large corpus of emotional speech …
approached from a deep transfer learning perspective. A large corpus of emotional speech …