Estonian Large Vocabulary Speech Recognition System for Radiology

Abstract

This paper describes implementation and evaluation of an Estonian large vocabulary continuous speech recognition system prototype for the radiology domain. We used a 44 million word corpus of radiology reports to build a word trigram language model. We recorded a test set of dictated radiology reports using ten radiologists. Using speaker independent speech recognition, we achieved a 9.8% word error rate. Recognition worked in around 0.5 real-time. One of the prominent sources of errors were mistakes in writing compound words.