Methods of
Informatics and Mathematics in a System for Dictating Thyroid Gland
Medical Reports
Kocsor A.,
Bánhalmi A., Paczolay D.
With the considerable development of
speech recognition technologies in several administration-requiring
professions the demand for the so called speech-based documentation
has grown. This is particularly true in the case of the documentation
of medical reports therefore the acceleration of this procedure is
of great importance. For smaller languages with special linguistic
features few systems for dictating medical reports have been developed
so far which fact can be attributed to linguistic specialties and
high development expenses. In Szeged we developed a core module capable of
automatic recognition of the Hungarian language on which several domain
oriented systems can be built. The core module contains the so called
acoustic model, which is suitable for the recognition of the Hungarian
phoneme set and representative modeling. For the building of the model
we used two significantly different approaches. One is the Hidden
Markov Model, well known in speech recognition, the other is the novel
stochastic segmental approach developed in Szeged. For the development
of both models we used a large speech corpus with 500 speakers, and
then the performance of the modules was tested on test databases.
To accompany the core module we built a language
module (for Windows environment) suitable for the dictation of thyroid
gland medical reports in order to justify the applicability of the
developed methods. The module was built on 9231 written thyroid medical
reports and over 2500 word forms. We present the structure of the developed system
for dictating thyroid gland medical reports, the technology of the
built language and acoustic models, the test results describing the
efficiency of the models, furthermore we mention the different aspects
of the application and technology of the software.
