语音情感识别使用openSMILE和GPT 3.5变压器
Darius Turcian1, Vasile Stoicu-Tivadar1
1Politehnica University Timişoara, Department of Automation and Applied Informatics, Timişoara, Romania.
Studies in health technology and informatics
|August 23, 2024
概括
这项研究引入了一种新的方法,使用人工智能和机器学习 (ML) 来检测罗马尼亚语中的情绪. 将语义和声学分析结合起来,实现了74%的准确性,为心理健康研究铺平了道路.
科学领域:
- 人工智能的人工智能
- 语音 情感 识别 语言
- 计算语言学 计算语言学
背景情况:
- 机器学习 (ML) 已经显著进步,改善了语音中的情感识别.
- 罗马尼亚语语音情感检测提出了独特的挑战和机遇.
研究的目的:
- 提出和评估一种新的方法来检测罗马尼亚语中的情绪.
- 将语义分析 (GPT Transformer) 和声学分析 (openSMILE) 结合起来,以提高准确性.
主要方法:
- 使用GPT转换器进行语音语义分析.
- 使用openSMILE工具包进行声学特征提取.
- 整合了这两种方法的混合情绪检测系统.
主要成果:
- 在情绪检测方面实现了74%的整体准确性.
- 获得了大约82%的精度率.
- 确定了影响性能的数据集限制 (大小,质量).
结论:
- 混合方法对罗马尼亚语语音情感识别有很大的希望.
- 未来的研究可以利用情绪分析来识别心理健康障碍.
- 数据集的增强对于提高系统的稳定性和准确性至关重要.
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