A Enhanced Speech Command Recognition using Convolutional Neural Networks

المؤلفون

DOI:

https://doi.org/10.31272/jeasd.28.6.8

الكلمات المفتاحية:

Convolutional Neural Network، Human voice، Machine voice، Mel-frequency cepstral coefficient

الملخص

يقدم هذا البحث نظام التعرف على الكلام المعتمد على شبكة (CNN) التي تستخدم معاملات ميل التردد الرأسي. يمكن للنظام التمييز بدقة بين أصوات الإنسان والأصوات الآلية عن طريق التقاط الصوت من خلال الميكروفون. في مجال الذكاء، في الأنظمة الذكية التي تستخدم تقنية التعرف على الكلام، يعد التفاعل بين البشر والآلات أمرًا بالغ الأهمية. لقد استكشفنا خيارات المعلمات الفائقة لتحسين بنية النموذج مما يسمح له بالتعرف بدقة على عشرة أوامر منطوقة مختلفة حتى في البيئات الصاخبة. استخدمنا مجموعة بيانات Google Speech لتدريب الشبكة وأظهرت النتائج معدلات دقة؛ 99.0319% للتدريب، 95.1124% للتحقق من الصحة، 95.9272% للاختبار. تشير هذه النتائج إلى أن هذا النظام لديه إمكانات للتطبيقات في سيناريوهات التعرف على الكلام في العالم الحقيقي.

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التنزيلات

Key Dates

الإستلام

2023-11-23

النسخة النهائية

2024-10-01

الموافقة

2024-10-19

النشر الالكتروني

2024-11-01

منشور

2024-11-01

كيفية الاقتباس

Kadhim, I. J., Tawfeeq E. Abdulabbas, Ali, R. ., Ali F. Hassoon, & Premaratne , P. (2024). A Enhanced Speech Command Recognition using Convolutional Neural Networks. مجلة الهندسة والتنمية المستدامة, 28(6), 754-761. https://doi.org/10.31272/jeasd.28.6.8

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