In this article, we present and evaluate a method for training a statistical part-of-speech tagger on data from written language and then adapting it to the requirements of tagging a corpus of transcribed spoken language, in our case spoken Swedish. This is currently a significant problem for many research groups working with spoken language, since the availability of tagged training data from spoken language is still very limited for most languages. The overall accuracy of the tagger developed for spoken Swedish is quite respectable, varying from 95% to 97% depending on the tagset used. In conclusion, we argue that the method presented here gives good tagging accuracy with relatively little effort.

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This paper argues for the usefulness of multimodal spoken language corpora and specifies components of a platform for the creation, maintenance and exploitation of such corpora. Two of the components, which have already been implemented as prototypes, are described in more detail: TransTool and SyncTool. TransTool is a transcription editor meant to facilitate and partially automate the task of a human transcriber, while SyncTool is a tool for aligning the resulting transcriptions with a digitized audio and video recording in order to allow synchronized presentation of different representations (e.g., text, audio, video, acoustic analysis). Finally, a brief comparison is made between these tools and other programs developed for similar purposes.

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