병리적 음성에 대한 성문 역 여과 분석의 유용성

다국어 초록 (Multilingual Abstract)

Purpose : In this study, we introduced Aalto Aparat, a piece of open-source software that can automatically execute glottal inverse filtering (GIF) and analyze various parameter values. We also tried to determine the usefulness of various parameters through normal and pathological voice analysis.
Methods : GIF analysis was performed on 20 normal adults and 20 with vocal nodules, and 20 with vocal cords palsy. Using Aalto Aparat, two steps required in the GIF study were inverse-filtered and converted into a glottal waveform, and the converted glottal waveform was analyzed in various ways. Analysis variables included open quotient (OQ), speed quotient (SQ), closing quotient (CLQ), amplitude quotient (AQ), and normalized amplitude quotient (NAQ), and quasi-open quotient (QOQ).
Results : By converting a general voice waveform into an LPC spectrum for converting to a glottal waveform, a glottal airflow waveform is obtained, and this waveform is integrated again to confirm that the glottal inverse filter analysis waveform is automatically analyzed without users special manipulation. The OQ, SQ, CIQ, AQ, NAQ, and QOQ values of normal speech using GIF were analyzed to establish a reference value. In addition, it was found that the values of AQ, CLQ and OQ are useful for distinguishing between pathological voice, vocal cord paralysis, vocal cord cysts and vocal cord nodules.
Conclusions : In this study, objective values of the glottal waveforms of normal adults were obtained, and these parameter values were applied to negative diseases to determine whether there was a difference from normal voices; it was found that the GIF value is useful for pathological voice diagnosis.

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