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Estonian Large Vocabulary Speech Recognition System for Radiology
Tanel Alumäe, Einar Meister
33 - 38
10.3233/978-1-60750-641-6-33
Frontiers in Artificial Intelligence and Applications
Volume 219: Human Language Technologies – The Baltic Perspective
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.

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