Attention guided 3D CNN-LSTM model for accurate speech based emotion recognition
In this paper, a novel approach, which is based on attention guided 3D convolutional neural
networks (CNN)-long short-term memory (LSTM) model, is proposed for speech based …
networks (CNN)-long short-term memory (LSTM) model, is proposed for speech based …
Automated accurate speech emotion recognition system using twine shuffle pattern and iterative neighborhood component analysis techniques
Speech emotion recognition is one of the challenging research issues in the knowledge-
based system and various methods have been recommended to reach high classification …
based system and various methods have been recommended to reach high classification …
Optimal feature selection based speech emotion recognition using two‐stream deep convolutional neural network
Speech signal processing is an active area of research, the most dominant source of
exchanging information among human beings, and the best way for human–computer …
exchanging information among human beings, and the best way for human–computer …
Variational mode decomposition based acoustic and entropy features for speech emotion recognition
Automated speech emotion recognition (SER) is a machine-based method for identifying
emotion from speech signals. SER has many practical applications, including improving …
emotion from speech signals. SER has many practical applications, including improving …
Chirplet transform based time frequency analysis of speech signal for automated speech emotion recognition
Nowadays, the recognition of emotion using the speech signal has gained popularity
because of its vast number of applications in different fields like medicine, online marketing …
because of its vast number of applications in different fields like medicine, online marketing …
GM-TCNet: Gated multi-scale temporal convolutional network using emotion causality for speech emotion recognition
JX Ye, XC Wen, XZ Wang, Y Xu, Y Luo, CL Wu… - Speech …, 2022 - Elsevier
In human-computer interaction, Speech Emotion Recognition (SER) plays an essential role
in understanding the user's intent and improving the interactive experience. While similar …
in understanding the user's intent and improving the interactive experience. While similar …
Aspect-based sentiment analysis of customer speech data using deep convolutional neural network and bilstm
S Murugaiyan, SR Uyyala - Cognitive Computation, 2023 - Springer
The process of detecting sentiments of particular context from human speech emotions is
naturally in-built for humans unlike computers, where it is not possible to process human …
naturally in-built for humans unlike computers, where it is not possible to process human …
An efficient speech emotion recognition based on a dual-stream CNN-transformer fusion network
The use of machine learning and artificial intelligence enables us to create intelligent
systems. Speech emotion recognition system analyzes the speaker's speech to determine …
systems. Speech emotion recognition system analyzes the speaker's speech to determine …
Speaker attentive speech emotion recognition
Speech Emotion Recognition (SER) task has known significant improvements over the last
years with the advent of Deep Neural Networks (DNNs). However, even the most successful …
years with the advent of Deep Neural Networks (DNNs). However, even the most successful …
Multi-branch feature learning based speech emotion recognition using SCAR-NET
K Mao, Y Wang, L Ren, J Zhang, J Qiu… - Connection Science, 2023 - Taylor & Francis
Speech emotion recognition (SER) is an active research area in affective computing.
Recognizing emotions from speech signals helps to assess human behaviour, which has …
Recognizing emotions from speech signals helps to assess human behaviour, which has …