An efficient mispronunciation detection system using discriminative acoustic phonetic features for Arabic consonants
المؤلفون المشاركون
Maqsud, Muazzam
Habib, Hifz
Nawaz, Tbassam
المصدر
The International Arab Journal of Information Technology
العدد
المجلد 16، العدد 2 (31 مارس/آذار 2019)، ص ص. 242-250، 9ص.
الناشر
تاريخ النشر
2019-03-31
دولة النشر
الأردن
عدد الصفحات
9
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الموضوعات
الملخص EN
Mispronunciation detection is an important component of Computer-Assisted Language Learning (CALL) systems.
It helps students to learn new languages and focus on their individual pronunciation problems.
In this paper, a novel discriminative Acoustic Phonetic Feature (APF) based technique is proposed to detect mispronunciations using artificial neural network classifier.
By using domain knowledge, Arabic consonants arecategorized into two groups based on their acoustic similarities.
The first group consists of consonants having similar ending sounds and the second group consists ofconsonants with completely different sounds.
In our proposed technique, the discriminative acoustic features are required for classifier training.
To extract these features, discriminativeparts of the Arabic consonants are identified.
As a test case, a dataset is collected from native/non-native, male / female and children of different ages.
This dataset comprises of 5600 isolated Arabic consonants.
The average accuracy of the system, when tested with simple acoustic features are found to be 73.57 %.While the use of discriminative acoustic features has improved the average accuracy to 82.27 %.
Some consonant pairs that are acoustically very similar, produced poor results and termed as Bad Phonemes.
A subjective analysis has also been carried out to verify the effectiveness of the proposed system.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Maqsud, Muazzam& Habib, Hifz& Nawaz, Tbassam. 2019. An efficient mispronunciation detection system using discriminative acoustic phonetic features for Arabic consonants. The International Arab Journal of Information Technology،Vol. 16, no. 2, pp.242-250.
https://search.emarefa.net/detail/BIM-854929
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Maqsud, Muazzam…[et al.]. An efficient mispronunciation detection system using discriminative acoustic phonetic features for Arabic consonants. The International Arab Journal of Information Technology Vol. 16, no. 2 (Mar. 2019), pp.242-250.
https://search.emarefa.net/detail/BIM-854929
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Maqsud, Muazzam& Habib, Hifz& Nawaz, Tbassam. An efficient mispronunciation detection system using discriminative acoustic phonetic features for Arabic consonants. The International Arab Journal of Information Technology. 2019. Vol. 16, no. 2, pp.242-250.
https://search.emarefa.net/detail/BIM-854929
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-854929
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