[HTML][HTML] Survey on bimodal speech emotion recognition from acoustic and linguistic information fusion
Speech emotion recognition (SER) is traditionally performed using merely acoustic
information. Acoustic features, commonly are extracted per frame, are mapped into emotion …
information. Acoustic features, commonly are extracted per frame, are mapped into emotion …
CubeMLP: An MLP-based model for multimodal sentiment analysis and depression estimation
Multimodal sentiment analysis and depression estimation are two important research topics
that aim to predict human mental states using multimodal data. Previous research has …
that aim to predict human mental states using multimodal data. Previous research has …
MEmoR: A multimodal emotion recognition using affective biomarkers for smart prediction of emotional health for people analytics in smart industries
The intersection of people, data and intelligent machines has a far-reaching impact on the
productivity, efficiency and operations of a smart industry. Internet-of-things (IoT) offers a …
productivity, efficiency and operations of a smart industry. Internet-of-things (IoT) offers a …
Real-time emotional health detection using fine-tuned transfer networks with multimodal fusion
Recognizing and regulating human emotion or a wave of riding emotions are a vital life skill
as it can play an important role in how a person thinks, behaves and acts. Accurate real-time …
as it can play an important role in how a person thinks, behaves and acts. Accurate real-time …
Modality-invariant temporal representation learning for multimodal sentiment classification
Multimodal sentiment classification is a notable research field that aims to refine sentimental
information and classify the sentiment tendency from sequential multimodal data. Most …
information and classify the sentiment tendency from sequential multimodal data. Most …
Sentiment analysis and emotion recognition from speech using universal speech representations
The study of understanding sentiment and emotion in speech is a challenging task in human
multimodal language. However, in certain cases, such as telephone calls, only audio data …
multimodal language. However, in certain cases, such as telephone calls, only audio data …
Multimodal emotion recognition with modality-pairwise unsupervised contrastive loss
Emotion recognition is involved in several real-world applications. With an increase in
available modalities, automatic understanding of emotions is being performed more …
available modalities, automatic understanding of emotions is being performed more …
Classification of sound using convolutional neural networks
A Chaturvedi, SA Yadav, HM Salman… - … and Informatics (IC3I …, 2022 - ieeexplore.ieee.org
Sound has a significant impact on every aspect of human life. The study of sound
classification has gained popularity recently across a wide range of fields. In a variety of …
classification has gained popularity recently across a wide range of fields. In a variety of …
Investigating Transformer Encoders and Fusion Strategies for Speech Emotion Recognition in Emergency Call Center Conversations.
There has been growing interest in using deep learning techniques to recognize emotions
from speech. However, real-life emotion datasets collected in call centers are relatively rare …
from speech. However, real-life emotion datasets collected in call centers are relatively rare …
Exploring attention mechanisms for multimodal emotion recognition in an emergency call center corpus
T Deschamps-Berger, L Lamel… - ICASSP 2023-2023 …, 2023 - ieeexplore.ieee.org
The emotion detection technology to enhance human decision-making is an important
research issue for real-world applications, but real-life emotion datasets are relatively rare …
research issue for real-world applications, but real-life emotion datasets are relatively rare …