Abstract
In this paper, two systems are proposed for the task of capitalisation generation. The first system is a slightly modified speech recogniser. In this system, every word in the vocabulary is duplicated: once in a decapitalised form and again in capitalised forms. In addition, the language model is re-trained on mixed case texts. The other system is based on Named Entity (NE) recognition and punctuation generation, since most capitalised words are first words in sentences or NE words. Both systems are compared for speech input. The system based on NE recognition and punctuation generation shows better results in Word Error Rate (WER) and in F-measure than the system modified from the speech recogniser.
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