A Novel Heterogeneous Parallel Convolution Bi-LSTM for Speech Emotion Recognition

A Novel Heterogeneous Parallel Convolution Bi-LSTM for Speech Emotion Recognition

Speech emotion recognition is a substantial component of natural language processing (NLP). It has strict requirements for the effectiveness of feature extraction and that of the acoustic model. With that in mind, a Heterogeneous Parallel Convolution Bi-LSTM model is proposed to address the challeng...

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Bibliographic Details
Main Authors: Huiyun Zhang, Heming Huang, Henry Han
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Applied Sciences
Subjects:
speech emotion recognition
feature extraction
heterogeneous parallel network
spectral features
prosodic features
multi-feature fusion
Online Access:https://www.mdpi.com/2076-3417/11/21/9897

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