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View all- Luo NWang Z(2024)The Use of Multi-Feature Fusion in the Evaluation of Emotional Expressions in Spoken EnglishApplied Mathematics and Nonlinear Sciences10.2478/amns-2024-23429:1Online publication date: 3-Sep-2024
To address the problem of low accuracy of unimodal speech emotion recognition methods, a bimodal MCNN-BiLSTM-Attention speech emotion recognition algorithm is proposed. The algorithm adopts the Mel-spectrogram and text information in audio as input, ...
A speech emotion recognition algorithm based on multi-feature and Multi-lingual fusion is proposed in order to resolve low recognition accuracy caused bylack of large speech dataset and low robustness of acoustic features in the recognition of ...
Recent years have witnessed the great progress for speech emotion recognition using deep convolutional neural networks (DCNNs). In order to improve the performance of speech emotion recognition, a novel feature fusion method is proposed. With going ...
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