Parsing Speech: A Neural Approach to Integrating Lexical and Acoustic-Prosodic Information
Table 5: Parse and disfluency detection F1 scores on the test set comparing to other reported results.
['Model', 'Parse', 'Disfl']
It is difficult to compare systems directly, because of the many differences in the experimental set-up. For example, the original \newciteCharniak2001 result (reporting F=85.9 for parsing and F=78.2 for disfluencies) leverages punctuation in the text stream, which is not realistic for speech transcripts and not used in most other work. Our work benefits from more text training material than others, but others benefit from gold part-of-speech tags. \newciteKahn2005 use a modified sentence segmentation. There are probably minor differences in handling of word fragments and scoring edit regions. Thus, this table primarily shows that our framework leads to more benefits from sentence-internal prosodic cues than others have obtained.