| 摘 要: 目前，现有的语音情感识别研究主要考虑在实验环境下收集语音数据进行情感识别，并没有考虑现实世界中存在各种噪声的影响。为此，考虑到噪声的影响，提出一种面向对抗攻击的鲁棒性语音情感识别方法，用于实现带有噪声的情感语音的分类。首先采用快速梯度符号法生成对抗数据，然后将真实数据和对抗数据进行混合，再将混合数据输入防御模块中进行模型的对抗攻击训练。最后，在IEMOCAP数据集上的实验结果表明，该方法用于语音情感识别能有效提高深度学习模型的鲁棒性和识别准确率。 |
| 关键词: 语音情感识别；鲁棒性；对抗攻击 |
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中图分类号: TP391
文献标识码: A
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| A Robust Speech Emotion Recognition Method for Confrontational Attacks |
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CHEN Gang1,2, CHEN Ji2, ZHANG Shiqing2, ZHAO Xiaoming1,2
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( 1. Faculty of Mechanical Engineering & Automation, Zhejiang Sci -Tech University, Hangzhou 310018, China;
2. Institute of Intelligent Information Processing, Taizhou University, Taizhou 318000, China)
904699855@qq.com; 1424179695@qq.com; tzczsq@163.com; tzxyzxm@163.com
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| Abstract: At present, the existing research on speech emotion recognition mainly considers speech data collection in an experimental environment for emotion recognition, without considering the influence of various noises in the real world. For this reason, considering the influence of noise, this paper proposes a robust speech emotion recognition method for confrontational attacks to realize classification of emotional speech with noise. Firstly, fast gradient sign method is used to generate confrontation data which is mixed with the real data. Then the mixed data is input into the defense module to conduct confrontation attack training of the model. Finally, experimental results on the IEMOCAP dataset show that the method used in speech emotion recognition can effectively improve the robustness and recognition accuracy of the deep learning model. |
| Keywords: speech emotion recognition; robustness; confrontational attack |
