A Joint Network Based on Interactive Attention for Speech Emotion Recognition 作者列表: 胡英,侯世静,杨华敏,黄浩,何亮 研究背景 语音情感识别(Speech Emotion Recognition,SER)指通过让机器检测和识别人类语音信号中如喜悦、愤怒、悲伤、惊讶、恐惧等多种情感类别。为了适用于如客服对话等说话人身份是不重要因素的真...
In this paper, we propose an end-to-end speech emotion recognition system using multi-level acoustic information with a newly designed co-attention module. We firstly extract multi-level acoustic information, including MFCC, spectrogram, and the embedded high-level acoustic information with CNN, BiL...
Speech emotion recognition is a kind of technology that uses computers to create the relationship between speech and emotion measurement, and provides computers with the ability to recognize and understand human emotions. Therefore, speech emo
Specifically, a cross-attention fusion (CAF) module is designed to integrate the dual-stream output for emotion recognition. Using different dual-stream encoders (fully training a text processing network and fine-tuning a pre-trained large language network), the CAF module ...
Using Convolutional Neural Networks in speech emotion recognition on the RAVDESS Audio Dataset. emotionaudio-filescnn-modelspeech-emotion-recognition UpdatedApr 12, 2021 Jupyter Notebook Code for Speech Emotion Recognition with Co-Attention based Multi-level Acoustic Information ...
摘要原文 The paper presents a Multi-Head Attention deep learning network for Speech Emotion Recognition (SER) using Log mel-Filter Bank Energies (LFBE) spectral features as the input. The multi-head attention along with the position embedding jointly attends to information from different representatio...
The experimental results indicated the significance and the efficiency of our proposed model have shown excessive assistance with the implementation of a real-time SER system. Hence, our model is capable of processing original speech signals for the emotion recognition that utilizes lightweight dilated ...
An ensemble 1D-CNN-LSTM-GRU model with data augmentation for speech emotion recognition Precise recognition of emotion from speech signals aids in enhancing human-computer interaction (HCI). The performance of a speech emotion recognition (SER... MR Ahmed,S Islam,AKMM Islam,... - 《Expert Syst...
BiLSTM is used to solve the problem of poor performance of long-term dependent learning features, and attention mechanism is used for only a few frames contain emotional features in the children speech signal. Compared with the related speech emotion recognition models such as LSTM-CNN and 2D-...
In the field of Human-Computer Interaction (HCI), Speech Emotion Recognition (SER) is not only a fundamental step towards intelligent interaction but also plays an important role in smart environments e.g., elderly home monitoring. Most deep learning based SER systems invariably focus on handling...