دوره 17، شماره 4 - ( 12-1399 )
جلد 17 شماره 4 صفحات 168-155 |
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BabaAli B, Rekabdar B. Off-line Arabic Handwritten Recognition Using a Novel Hybrid HMM-DNN Model. JSDP 2021; 17 (4) :155-168
URL: http://jsdp.rcisp.ac.ir/article-1-975-fa.html
URL: http://jsdp.rcisp.ac.ir/article-1-975-fa.html
باباعلی باقر، رکابدار بابک. بازشناسی دستنوشته برون‌خط عربی بر مبنای یک رویکرد تلفیقی جدید از مدل مخفی مارکوف و شبکه‌های عصبی ژرف. پردازش علائم و داده‌ها. 1399; 17 (4) :155-168
دانشکده ریاضی، آمار و علوم رایانه، دانشگاه تهران
چکیده: (2984 مشاهده)
مسأله مدل‌سازی و بازشناسی دستنوشته شباهت بسیار زیادی به مسأله مدل‌سازی و بازشناسی گفتار دارد. به همین علت می‌توان از رویکردهای به‌کار گرفته‌شده برای مسأله بازشناسی گفتار با اندکی تغییر در مراحل ابتدایی آن مانند استخراج ویژگی، برای بازشناسی دستنوشته نیز بهره برد. با گسترش رویکردهای ترکیبی HMM-DNN و استفاده از توابع هدف دنباله‌ای مانند MMI پیشرفت‌های قابل توجهی در حوزه بازشناسی گفتار حاصل شده است. این مقاله با استفاده از نرم‌افزار متنباز KALDI، که شهرت اصلی آن در حوزه بازشناسی گفتار و همچنین به‌کارگیری آخرین مدل‌های ترکیبی ارائه‌شده در آن، به‌کمک روش افزایش داده مدلی برای بازشناسی دستنوشته عربی ارائه داده است. این پژوهش بر روی دادگان KHATT انجام شده که نرخ خطای بازشناسی واژه را بر روی این دادگان به میزان 32/7 درصد مطلق کاهش داده است.
واژه‌های کلیدی: بازشناسی دستنوشته عربی، شبکه‌های عصبی ژرف، مدل مخفی مارکوف، نرم‌افزار متنباز KALDI
نوع مطالعه: كاربردي |
موضوع مقاله:
مقالات پردازش متن
دریافت: 1397/11/28 | پذیرش: 1398/6/11 | انتشار: 1399/12/4 | انتشار الکترونیک: 1399/12/4
دریافت: 1397/11/28 | پذیرش: 1398/6/11 | انتشار: 1399/12/4 | انتشار الکترونیک: 1399/12/4
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