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Stuttering is a speech impediment that is a very complex disorder. It is difficult to
diagnose and treat, and is of unknown initiation, despite the large number of studies in
this field. Stuttering can take many forms and varies from person to person, and it can
change under the influence of external factors. Diagnosing and treating speech disorders
such as stuttering requires from a speech therapist, not only good professional prepa-
ration, but also experience gained through research and practice in the field. The use
of acoustic methods in combination with elements of artificial intelligence makes it
possible to objectively assess the disorder, as well as to control the effects of treatment.
The main aim of the study was to present an algorithm for automatic recognition
of fillers disfluency in the statements of people who stutter. This is done on the basis of
their parameterized features in the amplitude-frequency space. The work provides as
well, exemplary results demonstrating their possibility and effectiveness. In order to verify
and optimize the procedures, the statements of seven stutterers with duration of 2 to
4 minutes were selected. Over 70% efficiency and predictability of automatic detection
of these disfluencies was achieved. The use of an automatic method in conjunction with
therapy for a stuttering person can give us the opportunity to objectively assess the
disorder, as well as to evaluate the progress of therapy.
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