Tagging Spoken Language Using Written Language Statistics

This paper reports on two experiments with a probabilistic part-of-speech tagger, trained on a tagged corpus of written Swedish, being used to tag a corpus of (transcribed) spoken Swedish. The results indicate that with very little adaptations an accuracy rate of 85 % can be achieved, with an accuracy rate for known words of 90%. In addition, two dierent treatments of pauses were explored but with no signi cant gain in accuracy under either condition.