Benefit of a Class-based Language Model for Real-time Closed-captioning of TV Ice-hockey Commentaries

AbstractThis article describes the real-time speech recognition system for closed-captioning of TV ice-hockey commentaries. Automatic transcription of TV commentary accompanying an ice-hockey match is usually a hard task due to the spontaneous speech of a commentator put often into a very loud background noise created by the public, music, siren, drums, whistle, etc. Data for building this system was collected from 41 matches that were played during World Championships in years 2000, 2001, and 2002 and were transmitted by the Czech TV channels. The real-time closed-captioning system is based on the class-based language model designed after careful analysis of training data and OOV words in new (till now unseen) commentaries with the goal to decrease an OOV (Out-Of-Vocabulary) rate and increase recognition accuracy.