Partial Parsing of Spontaneous Spoken French

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 ...

• Type: Conference
• Year: 2010
• Where: LREC
• Authors: Olivier Blanc, Matthieu Constant, Anne Dister, Patrick Watrin
• Keywords: Education, Lexical Multiword Units, LREC 2010, Speech Transcription, Spontaneous Speech Transcriptions