Speech Emotion Recognition Using Attention Model. [PDF]
Int J Environ Res Public Health, 2023 Speech emotion recognition is an important research topic that can help to maintain and improve public health and contribute towards the ongoing progress of healthcare technology.
Singh J, Saheer LB, Faust O.
europepmc +4 more sources
Multimodal transformer augmented fusion for speech emotion recognition. [PDF]
Front Neurorobot, 2023 Speech emotion recognition is challenging due to the subjectivity and ambiguity of emotion. In recent years, multimodal methods for speech emotion recognition have achieved promising results.
Wang Y +7 more
europepmc +2 more sources
Effects of Data Augmentations on Speech Emotion Recognition [PDF]
Sensors, 2022 Data augmentation techniques have recently gained more adoption in speech processing, including speech emotion recognition. Although more data tend to be more effective, there may be a trade-off in which more data will not provide a better model.
Bagus Tris Atmaja, Akira Sasou
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Human-Computer Interaction with a Real-Time Speech Emotion Recognition with Ensembling Techniques 1D Convolution Neural Network and Attention. [PDF]
Sensors (Basel), 2023 Emotions have a crucial function in the mental existence of humans. They are vital for identifying a person’s behaviour and mental condition. Speech Emotion Recognition (SER) is extracting a speaker’s emotional state from their speech signal.
Alsabhan W.
europepmc +2 more sources
Selective Acoustic Feature Enhancement for Speech Emotion Recognition With Noisy Speech. [PDF]
IEEE/ACM Trans Audio Speech Lang Process, 2023 A speech emotion recognition (SER) system deployed on a real-world application can encounter speech contaminated with unconstrained background noise.
Leem SG +4 more
europepmc +2 more sources
An enhanced speech emotion recognition using vision transformer
Scientific ReportsIn human–computer interaction systems, speech emotion recognition (SER) plays a crucial role because it enables computers to understand and react to users’ emotions.
Samson Akinpelu +2 more
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Speech Emotion Recognition Based on Two-Stream Deep Learning Model Using Korean Audio Information
Applied Sciences, 2023 Identifying a person’s emotions is an important element in communication. In particular, voice is a means of communication for easily and naturally expressing emotions.
A-Hyeon Jo, Keun-Chang Kwak
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Dawn of the Transformer Era in Speech Emotion Recognition: Closing the Valence Gap [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Recent advances in transformer-based architectures have shown promise in several machine learning tasks. In the audio domain, such architectures have been successfully utilised in the field of speech emotion recognition (SER).
Johannes Wagner +5 more
semanticscholar +1 more source
Speech Emotion Recognition with Co-Attention Based Multi-Level Acoustic Information [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2022 Speech Emotion Recognition (SER) aims to help the machine to understand human’s subjective emotion from only audio in-formation. However, extracting and utilizing comprehensive in-depth audio information is still a challenging task.
Heqing Zou +4 more
semanticscholar +1 more source
A Deep Learning Method Using Gender-Specific Features for Emotion Recognition
Sensors, 2023 Speech reflects people’s mental state and using a microphone sensor is a potential method for human–computer interaction. Speech recognition using this sensor is conducive to the diagnosis of mental illnesses.
Li-Min Zhang +5 more
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