Automatic Gender Detection Based on Characteristics of Vocal Folds for Mobile Healthcare System
المؤلفون المشاركون
Imran, Muhammad
Alhussein, Musaed
Abdul, Wadood
Ali, Zulfiqar
المصدر
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-05-10
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
An automatic gender detection may be useful in some cases of a mobile healthcare system.
For example, there are some pathologies, such as vocal fold cyst, which mainly occur in female patients.
If there is an automatic method for gender detection embedded into the system, it is easy for a healthcare professional to assess and prescribe appropriate medication to the patient.
In human voice production system, contribution of the vocal folds is very vital.
The length of the vocal folds is gender dependent; a male speaker has longer vocal folds than a female speaker.
Due to longer vocal folds, the voice of a male becomes heavy and, therefore, contains more voice intensity.
Based on this idea, a new type of time domain acoustic feature for automatic gender detection system is proposed in this paper.
The proposed feature measures the voice intensity by calculating the area under the modified voice contour to make the differentiation between males and females.
Two different databases are used to show that the proposed feature is independent of text, spoken language, dialect region, recording system, and environment.
The obtained results for clean and noisy speech are 98.27% and 96.55%, respectively.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Alhussein, Musaed& Ali, Zulfiqar& Imran, Muhammad& Abdul, Wadood. 2016. Automatic Gender Detection Based on Characteristics of Vocal Folds for Mobile Healthcare System. Mobile Information Systems،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1111602
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Alhussein, Musaed…[et al.]. Automatic Gender Detection Based on Characteristics of Vocal Folds for Mobile Healthcare System. Mobile Information Systems No. 2016 (2016), pp.1-12.
https://search.emarefa.net/detail/BIM-1111602
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Alhussein, Musaed& Ali, Zulfiqar& Imran, Muhammad& Abdul, Wadood. Automatic Gender Detection Based on Characteristics of Vocal Folds for Mobile Healthcare System. Mobile Information Systems. 2016. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1111602
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1111602
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر