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Maryam Momeni

Maryam Momeni

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0002-2548-1619
Education: PhD.
ScopusId: 55959639000
Faculty: Engineering
Address: Arak University


Speech signal analysis of alzheimer’s diseases in farsi using auditory model system
Alzheimer’s disease  Auditory model system  Spectro-temporal modulation  Support vector machine
Journal Cognitive Neurodynamics
Researchers Maryam Momeni ، Mahdiyeh Rahmani


In recent years, extensive studies have been conducted on the diagnosis of Alzheimer’s disease (AD) using the noninvasive speech signal recognition method. In this study, Farsi speech signals were analyzed using the auditory model system (AMS) in order to recognize AD. For this purpose, after the pre-processing of the speech signals and utilizing AMS, 4D outputs as function of time, frequency, rate, and scale range were obtained. The AMS outcomes were averaged in term of time to analyze the rate-frequency-scale for both groups, Alzheimer’s and healthy control subjects. Thereafter, the maximum of spectral and temporal modulation and frequency were extracted to classify by the support vector machine (SVM). The SVM achieves higher promising recognition accuracy with compare to prevalent approaches in the field of speech processing. The acceptable results demonstrate the applicability of the proposed algorithm in non-invasive and lowcost recognizing Alzheimer’s only using the few extracted features of the speech signal.