连续演讲中相对基本频率的自动化分析:三种处理管道的开发和比较
Mark Berardi1, Erin Tippit2, Yixiang Gao3
1Department of Communication Sciences and Disorders, University of Iowa, Iowa City, IA; Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany.
概括
开发了用于连续语音相对基本频率 (RFF) 分析的自动管道. 新型的aRFF-B管道有效处理大型数据集,帮助语音研究和临床应用.
科学领域:
- 语音科学 语言科学
- 声学语音学的声音学
- 语音研究 语音研究
背景情况:
- 相对基本频率 (RFF) 量化了在讲话时的喉张力和声力.
- 目前从连续语音中进行的RFF分析需要人工处理,限制了大规模的生态研究.
- 需要自动化方法来有效地分析连续语音中的RFF.
研究的目的:
- 开发和评估三种完全自动化的管道,用于从连续语音中进行RFF分析.
- 为了解决当前RFF衍生方法中手工处理的局限性.
- 为大数据集提供时间效率高的RFF分析.
主要方法:
- 对比了两个修改的自动化相对基本频率 (aRFF) -AP管道与一条复制手动分析的新型管道 (aRFF-B).
- 测试了82名女性参与者的母音-辅音-母音 (VCV) 发音管道,有和没有声声疲劳.
- 经过验证的自动化RFF测量与手动分析对其可靠性和准确性的验证.
主要成果:
- 与手动分析相比,所有三个自动化管道都表现出良好的可靠性 (r ≥ 0.84) 和有效性.
- 需要最小的手动校正 (<4%),主要用于摩擦识别.
- 新的aRFF-B管道显示了最低的样本拒绝率 (10%-25%),同时保持了高可靠性并使并行计算成为可能.
结论:
- 自动化管道,特别是aRFF-B,允许对广泛的连续语音数据进行时间高效的RFF分析.
- 这些进步消除了手工干预的需要,促进了大规模的语音研究.
- 开发的管道可以扩大RFF在语音研究和临床实践中的应用.
关键词:
语音努力 语音处理 语音评估
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