Artificial intelligence and machine learning for transcription and translation for media editing

Abstract

Dialog in a language unfamiliar to an editor poses obvious challenges during the media editing process. It is nearly impossible to edit media containing spoken dialog without a clear comprehension of the underlying language. The methods described here use a combination of artificial intelligence and machine learning models to generate a language proxy in which the dialog is translated into a language that is familiar to the media editor. The editor is then able to edit the media composition in their own language. To generate an edited media composition with spoken dialog in the original language, the edited language proxy is synchronized with and linked back to the original media. The methods combine automatic speech recognition, translation, speech to text, and voice cloning together with existing non-AI technologies such as captioning and media relinking.