CorpusViz: Child and Adult Speech Visualisation

Jesse Tran, Quang Vinh Nguyen, Caroline Jones, Rachel Hendery, S. Simoff
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Abstract

Speech and language researchers often rely on large, naturalistic, audio-visual corpora to identify and measure patterns of language structure, variation, change and use. There are, however, few visualization tools designed for this need. This paper proposes a novel visual analytic method to process large linguistic corpora by employing Bayes' Theorem and interactive visualization. We adopt a simple and meaningful design in our visualization for linguists to understand. Instead of offering a fixed visualization, this project enables greater interaction through filtering, grouping and dragging. Multiple phases are included in the system, from processing the metadata exported from popular standalone linguistic software, to creating the visualization, and enabling interaction and filtering.
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CorpusViz:儿童和成人语言可视化
言语和语言研究人员经常依靠大型的、自然的、视听的语料库来识别和测量语言结构、变异、变化和使用的模式。然而,为满足这种需求而设计的可视化工具很少。本文提出了一种利用贝叶斯定理和交互可视化技术处理大型语料库的可视化分析方法。我们在可视化中采用了简单而有意义的设计,便于语言学家理解。这个项目没有提供固定的可视化,而是通过过滤、分组和拖动实现了更大的交互性。该系统包含多个阶段,从处理从流行的独立语言软件导出的元数据,到创建可视化,以及启用交互和过滤。
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