Development of a Hungarian Medical Dictation System

This paper reviews the current state of a Hungarian project which seeks to create a speech recognition system for the dictation of thyroid gland medical reports. First, we present the MRBA speech corpus that was assembled to support the training of general-purpose Hungarian speech recognition systems. Then we describe the processing of medical reports that were collected to help the creation of domain-specific language models. At the acoustic modelling level we experimented with two techniques – a conventional HMM one and an ANN-based solution – which are both briefly described in the paper. Finally, we present the language modelling methodology currently applied in the system, and round off with recognition results on test data taken from four speakers. The scores show that on a somewhat restricted sub-domain of the task we are able to produce word accuracies well over 95%.