Punctuation Prediction in Spontaneous Conversations: Can We Mitigate ASR Errors with Retrofitted Word Embeddings?
Table 1: The distribution of punctuation classes in the Fisher corpus.
['[BOLD] Class', '[BOLD] Count', '[BOLD] Percentage']
Our primary training data is the Fisher corpus [cieri2004fisher] due to its adequately punctuated transcripts. The Fisher corpus creation protocol relied upon a vast number of participants, each making a few short calls. Typically, the speakers would not know each other personally, which maximized inter-speaker variation and vocabulary breadth, although it also increased the formality of speech. The goal was to provide a representative distribution of subjects across a variety of demographic categories, including gender, age, dialect region, and English fluency. Hence, the Fisher corpus is a proper training and evaluation dataset for the punctuation prediction in the ASR transcripts.