Essential for converting spoken words into readable text (e.g., changing spoken numbers into digits).
Automated insertion of periods, commas, and question marks to improve readability, crucial for accurate comprehension of live news. Limitations Broadcast Subtiitrid Eesti
Deep learning models tailored for the Estonian language's phonetic structure. Essential for converting spoken words into readable text (e
Estonian Public Television (ERR) utilizes these systems for live broadcasts, and the Estonian Parliament uses them for live video feeds of parliamentary sessions. Performance Metrics (Quality Analysis) Estonian Public Television (ERR) utilizes these systems for
This paper describes a speech recognition based closed captioning system for Esto- nian language, primarily intended for the hard- OpenReview
Error rates increase to roughly 13.4% , indicating that specialized vocabulary, multiple speakers, or spontaneous speech can still pose challenges to the model. Technological Components
The systems show high reliability in controlled, professional environments like parliament, which often feature clear, structured speech. Error Rates: