Improving Data Driven Inverse Text Normalization using Data Augmentation. (arXiv:2207.09674v1 [cs.CL])

Inverse text normalization (ITN) is used to convert the spoken form output of
an automatic speech recognition (ASR) system to a written form. Traditional
handcrafted ITN rules can be complex to transcribe and maintain. Meanwhile
neural modeling approaches require quality large-scale spoken-written pair
examples in the same or similar domain as the ASR system (in-domain data), to
train. Both these approaches require costly and complex annotations. In this
paper, we present a data augmentation technique that effectively generates rich
spoken-written …

arxiv augmentation data normalization text