دوره 14، شماره 4 - ( 12-1396 )                   جلد 14 شماره 4 صفحات 143-157 | برگشت به فهرست نسخه ها

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Jafari H S, homayounpour M. A comparison of machine learning techniques for Persian Extractive Speech to Speech Summarization without Transcript. JSDP. 2018; 14 (4) :143-157
URL: http://jsdp.rcisp.ac.ir/article-1-491-fa.html
جعفری هدی سادات، همایون پور محمدمهدی. مقایسه روش‌های مختلف یادگیری ماشین در خلاصه‌سازی استخراجی گفتار به گفتار فارسی بدون استفاده از رونوشت. پردازش علائم و داده‌ها. 1396; 14 (4) :143-157

URL: http://jsdp.rcisp.ac.ir/article-1-491-fa.html


کارشناسی ارشد دانشگاه صنعتی امیرکبیر
چکیده:   (348 مشاهده)

در این مقاله، خلاصه‌سازی استخراجی گفتار با استفاده از روش‌های مختلف یادگیری ماشین مورد مطالعه قرار گرفته است. خلاصه‌سازی یک فایل گفتاری به معنای استخراج بخش‌های مهم و شاخص گفتار به‌منظور  دسترسی، جستجو، استخراج و مرورگری آسان‌تر و کم‌هزینه‌تر اطلاعات فایل‌های گفتاری است. در این مقاله، یک روش جدید خلاصه‌سازی گفتار بدون استفاده از سامانه بازشناسی خودکار گفتار ارائه شده است. الگوهای تکراری بین دو جمله گفتاری با استفاده از الگوریتم S-DTW، به‌طورمستقیم از روی سیگنال گفتار شناسایی می‌شوند. بعد از تعیین شباهت بین دو جمله و استخراج تعدادی ویژگی از هر جمله تأثیر روش‌های مختلف یادگیری ماشین، بانظارت، بی‌نظارت و نیمه‌نظارتی مورد بررسی قرار گرفته است. آزمایش‌ها برروی یک پیکره خوانده‌شده اخبار فارسی انجام شده است. نتایج نشان می‌دهد با استفاده از  ویژگی‌های مناسب، بدون استفاده از رونوشت به کارایی بالاتری نسبت به روش‌های پایه (3٪ افزایش در مقایسه با انتخاب نخستین جملات و 5٪ افزایش در مفایسه با انتخاب طولانی‌ترین جملات با استفاده از معیار ROUGE-3) می‌توان دست پیدا کرد.
 

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نوع مطالعه: كاربردي | موضوع مقاله: مقالات پردازش گفتار
دریافت: ۱۳۹۴/۱۱/۲۹ | پذیرش: ۱۳۹۶/۳/۲۰ | انتشار: ۱۳۹۶/۱۲/۲۲ | انتشار الکترونیک: ۱۳۹۶/۱۲/۲۲

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