Application of Speech Processing for Pathological Voice Detection and Analysis


Authors : Smitha S M; Prema K N; Roopa B S

Volume/Issue : Volume 7 - 2022, Issue 4 - April

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3sRRS8W

DOI : https://doi.org/10.5281/zenodo.6571357

In recent years, speech pathology analysis has played a big role in the announcements of doctors. so as to speak with an individual and categorical our thoughts and feelings, the speaker must act with the auditor by manufacturing speech input, that any is taken by the auditor and work is allotted consequently. The method by that thoughts area unit translated into speech involves the utilization of articulators for manufacturing numerous speech sounds. Speech defect may be a upset that's caused thanks to lack of management of assorted organs that area unit employed in the assembly of speech. The popularity and allocations of tone of pathological voices area unit believed as a difficult add the sector of speech analysis still currently. Which creates the requirement to search out some technology to assist the voice expert in police investigation the voice pathology? Such technological support may be done supported the entire understanding or learning of the foremost frequent vocal disorders, their symptoms, real cause and malady aspect results. Acoustic pointers, as well as variables such as transmission energy, pitch, silence removal, windowing, Mel consistency, amplitude Cepstrum, and jitter, are used to analyze the spoken signal..At the ultimate finish, the classification strategy i.e. Support vector machines are utilized to identify the quality and pathological speech, based on the options extracted in the previous section. The Speech pathology recognition system could successfully categorise and tag the standard tone of voice and the pathological speech which contributed to diagnosing the patient.

Keywords : Pathological, Cepstrum, Support Vector Machine, spectrogram.

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