دوره 14، شماره 4 - ( 12-1396 )
جلد 14 شماره 4 صفحات 157-143 |
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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
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
دانشگاه صنعتی امیرکبیر
چکیده: (5365 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.
واژه‌های کلیدی: خلاصه‌سازی استخراجی گفتار، سیگنال گفتار، الگوها کلیدی، الگوریتم S-DTW، یادگیری ماشین
نوع مطالعه: كاربردي |
موضوع مقاله:
مقالات پردازش گفتار
دریافت: 1394/11/29 | پذیرش: 1396/3/20 | انتشار: 1396/12/22 | انتشار الکترونیک: 1396/12/22
دریافت: 1394/11/29 | پذیرش: 1396/3/20 | انتشار: 1396/12/22 | انتشار الکترونیک: 1396/12/22
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