Multimodal Approach of Speech Emotion Recognition Using Multi-Level Multi-Head Fusion Attention-Based Recurrent Neural Network

Speech emotion recognition is a challenging but important task in human computer interaction (HCI). As technology and understanding of emotion are progressing, it is necessary to design robust and reliable emotion recognition systems that are suitable for real-world applications both to enhance anal...

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Veröffentlicht in:	IEEE access 2020, Vol.8, p.61672-61686
Hauptverfasser:	Ho, Ngoc-Huynh, Yang, Hyung-Jeong, Kim, Soo-Hyung, Lee, Gueesang
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms audio features Bit error rate Coders Datasets Decision analysis Decision making Emotion recognition Emotions Feature extraction Hidden Markov models Human performance Human-computer interface Mel frequency cepstral coefficient Motion capture multi-level multi-head fusion attention Neural networks Recurrent neural networks RNN Speech emotion recognition Speech recognition textual features
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