Automatic database segmentation using hybrid spectrum-visual approach
العناوين الأخرى
التقسيم الآلي لقاعدة البيانات باستخدام الطيف الهجين والنهج البصري
المؤلفون المشاركون
Judi, Amr Muhammad Rifat
Nashat, Ahmad Ali
al-Shaykh, Jamal Ahmad
Jubayli, Manar Uthman
المصدر
The Egyptian Journal of Language Engineering
العدد
المجلد 8، العدد 2 (30 سبتمبر/أيلول 2021)، ص ص. 28-43، 16ص.
الناشر
تاريخ النشر
2021-09-30
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الموضوعات
الملخص EN
Nowadays automated segmentation of speech signals has been attracted many of researchers all-over the world, Many speech processing systems require segmentation of speech waveform into principal acoustic units.
In this research, TIMIT DataBase (DB) is utilized to carry on this process and justify its operation or results.
Thus, this paper presents a novel method of segmentation of speech phonemes, where the proposed strategy helps in the selection of appropriate feature extraction technique for speech segmentation.
There are three main techniques of feature extraction used in our research; the first technique is the Mel Frequency Cepstral Coefficient (MFCC), the second technique is known by Best Tree Encoding (BTE), while the third is Image Normalized Encoder (INE), which is a hybrid technique between the Best Tree Image (BTI), and the Convolution Neural Network (CNN) ResNet-50.
Then, data are trained using a hybrid model that consists of Hidden Markov Model (HMM), and Gaussian Mixture Model (GMM) to improve the performance of automatic speech recognition.
The proposed model is tested and verified against the most widely used feature Mel Frequency Cepstral Coefficient (MFCC) plus delta and delta-delta coefficients (39 parameters) to evaluate its performance.
This approach has the potential to be used in applications such as automatic speech recognition and automatic language identification.
The experimental results show that BTE technique achieved the highest success rate (?) (92.64% ) than using the (INE) technique.
However, the INE technique gives confusion success rate for Tr and NTr of values 97.1% and 99.1% , respectively.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jubayli, Manar Uthman& Judi, Amr Muhammad Rifat& al-Shaykh, Jamal Ahmad& Nashat, Ahmad Ali. 2021. Automatic database segmentation using hybrid spectrum-visual approach. The Egyptian Journal of Language Engineering،Vol. 8, no. 2, pp.28-43.
https://search.emarefa.net/detail/BIM-1307144
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Nashat, Ahmad Ali…[et al.]. Automatic database segmentation using hybrid spectrum-visual approach. The Egyptian Journal of Language Engineering Vol. 8, no. 2 (Sep. 2021), pp.28-43.
https://search.emarefa.net/detail/BIM-1307144
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jubayli, Manar Uthman& Judi, Amr Muhammad Rifat& al-Shaykh, Jamal Ahmad& Nashat, Ahmad Ali. Automatic database segmentation using hybrid spectrum-visual approach. The Egyptian Journal of Language Engineering. 2021. Vol. 8, no. 2, pp.28-43.
https://search.emarefa.net/detail/BIM-1307144
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
-
رقم السجل
BIM-1307144
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