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This paper is motivated by the automation of neuropsychological testsinvolving discourse analysis in the retellings of narratives by patients withpotential cognitive impairment. In this scenario the task of sentence boundarydetection in speech transcripts is important as discourse analysis involves theapplication of Natural Language Processing tools, such as taggers and parsers,which depend on the sentence as a processing unit. Our aim in this paper is toverify which embedding induction method works best for the sentence boundarydetection task, specifically whether it be those which were proposed to capturesemantic, syntactic or morphological similarities.

Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts