Automated transcription services turn audio, video, and graphic content into text so artificial intelligence systems can process it more easily.
This kind of transcription, as opposed to manual transcription, transforms contents of various kinds into textual data, which can be more easily processed by machine learning models.
Audio data is identified using descriptive meta tags, making it immediately recognizable to algorithms. Voice data is typically extracted from recorded interviews, customer service calls, recordings and calls to virtual assistants. Visual and graphical data is annotated, processed and transcribed directly into text.
Audio transcription is used to train algorithms to identify sounds in voice tracks for various multilingual combinations.
Annotation and transcription of visual data enhances computer vision and pattern recognition systems.
The voice transcription activity is useful to train speech recognition algorithms and chatbots to make the user experience better.