对儿童和成人的方言密度估计的探索性研究 (A exploratory study on dialect density estimation for children and adults's African American
Alexander Johnson1, Natarajan Balaji Shankar1, Mari Ostendorf2
1Department of Electrical and Computer Engineering, University of California, Los Angeles, Los Angeles, California 90095, USA.
The Journal of the Acoustical Society of America
|April 29, 2024
概括
这项研究引入了一种新的框架,用于预测儿童和成人中非洲裔美国人英语方言密度. 该方法准确地分类方言级别,比二进制方法提供更大的特异性.
科学领域:
- 计算语言学 计算语言学
- 语音处理 语音处理
- 社会语言学 社会语言学
背景情况:
- 方言密度,方言特定特征的频率,对于细微的语音分析至关重要.
- 现有的方法经常使用二进制分类,缺乏对方言变化的特异性.
- 了解方言密度对于教育,法医和人工智能的应用至关重要.
研究的目的:
- 开发和评估一种用于预测非洲裔美国人英语口语密度的创新框架.
- 超越二进制分类,向更具体的方言密度水平预测.
- 分析影响机器对方言感知的声学和语法线索.
主要方法:
- 使用了来自HUBERT的自我监督学习表示.
- 从自动语音识别 (ASR) 副本中提取手工制作的基于语法的特征.
- 集成的形特征和其他特征集.
- 训练了一个XGBoost分类器来预测短语发言的方言密度标签.
主要成果:
- 在儿童和成年非洲裔美国人英语演讲中实现了方言密度的高分类准确性.
- 在不同年龄组和区域方言中表现出强的表现.
- 建立了分析影响方言知觉的声学和语法线索的基础.
结论:
- 拟议的框架有效地预测了高准确度的口语方言密度.
- 该方法提供了与二进制方法相比,方言特征的更具体的测量方法.
- 这项研究提供了对影响机器对方言感知的语言和声学因素的见解.
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