predicting from ASR output Features extracted from ASR transcripts are distinct from those extracted from human transcripts in at least three ways: (1) incorrectly recognized words incur erroneous lexical cohesion features (LF), (2) incorrectly recognized words incur erroneous cue phrase features (CUE), and (3) the ASR system recognizes less overlapping speech (OVR).
to the finding that integrating conversational features with lexical cohesion features is useful for prediction from human transcripts, Table 3 shows that when operating on ASR output, neither adding interactional nor cue phrase features improves the performance of the model using only lexical cohesion features.