Boosting Transcript Readability with Automatic Punctuation and Casing and ITN

This text discusses the process of automatic punctuation and casing in transcription texts using the AssemblyAI Speech-to-Text API. It explains how the model is trained on a large dataset to predict proper punctuation and casing, making it easier for users to read transcriptions. The text also introduces Inverse Text Normalization (ITN), which translates spoken form of text into its written form. The accuracy of the Punctuation and Casing Model is mentioned as being 93.5%, well above industry standards. The text concludes by discussing future model updates and improvements.