Partial Parsing of Spontaneous Spoken French
Olivier Blanc, Mathieu Constant, Anne Dister, Patrick Watrin · 2010
This paper describes the process and the resources used to automatically annotate a French corpus of spontaneous speech transcriptions in super-chunks.Super-chunks are enhanced chunks that can contain lexical multiword units.This partial parsing is based on a preprocessing stage of the spoken data that consists in reformatting and tagging utterances that break the syntactic structure of the text, such as disfluencies.Spoken specificities were formalized thanks to a systematic linguistic study of a 40-hour-long speech transcription corpus.The chunker uses large-coverage and fine-grained language resources for general written language that have been augmented with resources specific to spoken French.It consists in iteratively applying finite-state lexical and syntactic resources and outputing a finite automaton representing all possible chunk analyses.The best path is then selected thanks to a hybrid disambiguation stage.We show that our system reaches scores that are comparable with state-of-the-art results in the field.