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Prosodic event detection in children's read speech

机译：儿童阅读语音中的韵律事件检测

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摘要

Prosody is the supra-segmental aspect of speech that helps to convey the structure and intended meaning of lexical content unambiguously. The automatic detection of prosodic events, such as phrase boundary and word prominence, has a number of applications in discourse analysis, where a combination of syntactic and acoustic-prosodic features is typically employed. This work addresses prosodic event detection in the context of assessing oral reading skills of middle-school children. We discuss the observed characteristics of a specially created labeled data set of oral reading recordings of English stories by non-native speakers. The obtained diversity of language skills adds to the known challenges of high speaker variability in the acoustic realization of prosodic events. A combination of knowledge- and data-driven feature selection is implemented to identify a compact set of word-level features from the acoustic correlates of prosody considering different ways of incorporating the necessary temporal context The system is benchmarked with reference to a widely known prosodic event recognition system in a speaker-independent set-up to obtain a competitive performance with greatly reduced feature dimensionality. The interpretable features enable us to use the predictor model importance scores to identify high-level speaker traits that influence the acoustic realization of prosodic events, suggesting a potential extension to systems that can extract and utilize speaker idiosyncrasies for superior prosodic event detection.
机译：韵律是言语的同步分段方面，有助于明确地传达词汇含量的结构和预期的含义。韵律事件（例如短语边界和字突出）的自动检测在话语分析中具有许多应用，其中通常采用句法和声学 - 韵律特征的组合。这项工作解决了评估中学儿童口头阅读技巧的背景下的韵律事件检测。我们讨论了非母语人士对英语故事的专门创建标记数据集的观察到的特征。所获得的语言技能多样性增加了韵律事件声学实现中高位扬声器变异的已知挑战。实现了知识和数据驱动特征选择的组合，以识别来自考虑到结合必要的时间上下文的不同方式的韵律的声学相关的紧凑型词级特征，该系统参考众所周知的韵律事件基准测试识别系统在扬声器独立的设置中，以获得具有大大减少特征维度的竞争性能。可解释的功能使我们能够利用预测的模型重要性分数来识别影响韵律事件的声学实现的高级扬声器特征，这表明可以提取和利用扬声器特质的系统的潜在扩展，以用于卓越的韵律事件检测。

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