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date: 04 July 2020

Abstract and Keywords

Empirical research often involves three activities: the systematic annotation of audiovisual media (coding), the management of the resulting data in a corpus, and various forms of statistical analysis. This chapter presents ANVIL, a highly generic and theory-independent research tool that supports all three activities in conjunction with audio, video, and 3D motion capture data. The tool allows to specify a formal coding scheme as a blueprint for project-specific coding. The process of coding is conducted on parallel time-aligned tracks. Instead of simple tags, ANVIL offers typed attributes for describing the basic annotation elements which can be used to hide away complexity and reduce visual clutter. Track types (interval vs. point) and logical track relationships (singleton, span, subdivision) further increase the clarity and consistency of the coding. Spatial mark-up on the video frame allows annotation of regions over time. For corpus management, ANVIL allows annotation files to be grouped into projects for browsing, export, and analysis across a corpus of data. For analysis, the tool supports simple descriptive analyses like transition diagrams or label frequency histograms and more complex operations like automatic inter-coder agreement computation (Cohen’s kappa).

Keywords: annotation tool, behaviour analysis, motion capture, gesture research, coding reliability

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