A Tool for Feature-Structure Stand-Off-Annotation on Transcriptions of Spoken Discourse

Abstract

Annotation Science, a discipline dedicated to developing and maturing methodology for the annotation of language resources, is playing a prominent role in the fields of computational and corpus linguistics. While progress in the search for the right annotation model and format is undeniable, these results only sparsely become manifest in actual solutions (i.e. software tools) that could be used by researchers wishing to annotate their resources right away, even less so for resources of spoken language transcriptions. The paper presents a solution consisting of a data model and an annotation tool that tries to fill this gap between „annotation science“ and the practice of transcribing spoken language in the area of discourse analysis and pragmatics, where the lack of ready-to-use annotation solutions is especially remarkable. The chosen model combines feature structures in standoff-annotation and a data model based on annotation graphs, combining their advantages. It is ideally fitted for the transcription of spoken language by centering on the temporal relations of the speaker’s utterances and is implemented in reliable tools that support an iterative workflow. The standoff annotation allows for more complex annotations and relies on an established and well documented model.

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