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Cenk Demiroglu
Researcher at Özyeğin University
Publications - 43
Citations - 477
Cenk Demiroglu is an academic researcher from Özyeğin University. The author has contributed to research in topics: Speech synthesis & Speaker recognition. The author has an hindex of 9, co-authored 38 publications receiving 327 citations. Previous affiliations of Cenk Demiroglu include Istanbul University.
Papers
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Proceedings ArticleDOI
Parkinson’s Disease Diagnosis Using Machine Learning and Voice
TL;DR: This paper explores the effectiveness of using supervised classification algorithms, such as deep neural networks, to accurately diagnose individuals with the disease, and provides evidence to validate this concept here using a voice dataset collected from people with and without PD.
Journal ArticleDOI
Anti-spoofing for text-independent speaker verification: an initial database, comparison of countermeasures, and human performance
Zhizheng Wu,Phillip L. De Leon,Cenk Demiroglu,Ali Khodabakhsh,Simon King,Zhen-Hua Ling,Daisuke Saito,Bryan Stewart,Tomoki Toda,Mirjam Wester,Junichi Yamagishi +10 more
TL;DR: This paper starts with a thorough analysis of the spoofing effects of five speech synthesis and eight voice conversion systems, and the vulnerability of three speaker verification systems under those attacks, and introduces a number of countermeasures to prevent spoofing attacks.
Proceedings ArticleDOI
SAS: A speaker verification spoofing database containing diverse attacks
Zhizheng Wu,Ali Khodabakhsh,Cenk Demiroglu,Junichi Yamagishi,Daisuke Saito,Tomoki Toda,Simon King +6 more
TL;DR: The first version of a speaker verification spoofing and anti-spoofing database, named SAS corpus, is presented, which includes nine spoofing techniques, two of which are speech synthesis, and seven are voice conversion.
Journal ArticleDOI
Evaluation of linguistic and prosodic features for detection of Alzheimer’s disease in Turkish conversational speech
TL;DR: Experimental results show that the proposed features extracted from the speech signal can be used to discriminate between the control group and the patients with Alzheimer’s disease.
Journal ArticleDOI
Depression Screening from Voice Samples of Patients Affected by Parkinson's Disease.
Yasin Ozkanca,Mirac Goksu Ozturk,Merve Nur Ekmekci,David C. Atkins,Cenk Demiroglu,Reza Hosseini Ghomi +5 more
TL;DR: Voice may be an effective digital biomarker to screen for depression among Parkinson’s disease patients and a clear correlation between feeling depressed and PD severity is indicated.