FIELD: diagnostic medicine.
SUBSTANCE: invention relates to means that provide automated performance of diagnostic procedures in terms of performing pre-medical assessment of the quality of speech recognition and screening audiometry using algorithms based on machine learning. A test speech sequence is formed in the form of words and/or phrases with a given volume level and in a given language based on a matrix test that supports the selected language. The test speech sequence is reproduced using a speech simulation based on a deep machine learning model. A noise competing sound is selected for the said test speech sequence of words. The levels of the useful signal of the test speech sequence and noise are controlled separately. An oral response from the user is received using a speech input device. In the automated mode, the user's oral response is automatically converted into a text form; the user's oral response is analyzed.
EFFECT: technical result is the provision of pre-medical assessment of speech recognition quality in noise and screening audiometry based on a single computing device.
19 cl, 9 dwg
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Authors
Dates
2021-02-15—Published
2020-09-07—Filed