J Zhao, X Mao, L Chen - Biomedical signal processing and control, 2019 - Elsevier
We aimed at learning deep emotion features to recognize speech emotion. Two convolutional neural network and long short-term memory (CNN LSTM) networks, one 1D …
K Kaur, P Singh - Multimedia Tools and Applications, 2023 - Springer
Among the other modes of communication, such as text, body language, facial expressions, and so on, human beings employ speech as the most common. It contains a great deal of …
This paper presents a multimodal emotion recognition system, which is based on the analysis of audio and visual cues. From the audio channel, Mel-Frequency Cepstral …
S Jothimani, K Premalatha - Chaos, Solitons & Fractals, 2022 - Elsevier
Abstract The Speech Emotion Recognition (SER) is a complex task because of the feature selections that reflect the emotion from the human speech. The SER plays a vital role and is …
S Zhang, X Tao, Y Chuang, X Zhao - Speech Communication, 2021 - Elsevier
Recently, spontaneous speech emotion recognition has become an active and challenging research subject. This paper proposes a new method of spontaneous speech emotion …
Despite the widespread use of supervised learning methods for speech emotion recognition, they are severely restricted due to the lack of sufficient amount of labelled speech data for …
Speech emotion recognition is the crucial stream in emotional computing and also create few issues owing to its complication in processing. The efficiency of the acoustic methods …
S Zhang, X Zhao, Q Tian - IEEE Transactions on Affective …, 2019 - ieeexplore.ieee.org
Recently, emotion recognition in real sceneries such as in the wild has attracted extensive attention in affective computing, because existing spontaneous emotions in real sceneries …
Speech emotion recognition (SER) systems find applications in various fields such as healthcare, education, and security and defense. A major drawback of these systems is their …