检索结果-南通市图书馆

Self-supervised Learning for Speech Emotion Recognition Task Using Audio-visual Features and Distil Hubert Model on BAVED and RAVDESS Databases

引用

Journal of Systems Science and Systems Engineering 2024年第5期33卷 576-606页

作者： Karim Dabbabi abdelkarim mars Research Unite of Analyse and Processing of Electrical and Energetic Systems Faculty of Sciences of TunisTunis El-Manar University2092Tunis-Tunisia Research Laboratory in Algebra Numbers Theory and Intelligent SystemsFaculty of Sciences of Monastir90 Mohamed V street5000-MonastirTunisia

Existing pre-trained models like Distil HuBERT excel at uncovering hidden patterns and facilitating accurate recognition across diverse data types, such as audio and visual information. We harnessed this capability to develop a deep learning model that utilizes Distil HuBERT for jointly learning these combined features in speech emotion recognition (SER). Our experiments highlight its distinct advantages: it significantly outperforms Wav2vec 2.0 in both offline and real-time accuracy on RAVDESS and BAVED datasets. Although slightly trailing HuBERT’s offline accuracy, Distil HuBERT shines with comparable performance at a fraction of the model size, making it an ideal choice for resource-constrained environments like mobile devices. This smaller size does come with a slight trade-off: Distil HuBERT achieved notable accuracy in offline evaluation, with 96.33% on the BAVED database and 87.01% on the RAVDESS database. In real-time evaluation, the accuracy decreased to 79.3% on the BAVED database and 77.87% on the RAVDESS database. This decrease is likely a result of the challenges associated with real-time processing, including latency and noise, but still demonstrates strong performance in practical scenarios. Therefore, Distil HuBERT emerges as a compelling choice for SER, especially when prioritizing accuracy over real-time processing. Its compact size further enhances its potential for resource-limited settings, making it a versatile tool for a wide range of applications.

关键词： Wav2vec 2.0 Distil HuBERT HuBERT SER audio and audio-visual features

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：