سال انتشار: ۱۳۹۰

محل انتشار: همایش ملی کامپیوتر و فناوری اطلاعات

تعداد صفحات: ۵

نویسنده(ها):

Mohsen Kazemian – MSc.) Department of Electrical EngineeringIslamic Azad University, Kerman, Iran
Amir Reza Sharifi Pur Shirazi – MSc.) Young Researchers Club, Shiraz Branch Islamic Azad University, Shiraz, Iran

چکیده:

Phonetic speech retrieval is used to augment word based retrieval in spoken document retrieval systems, for in and out of vocabulary words. In this paper, we present a new indexing and ranking scheme using metaphones and a Bayesian phonetic edit distance. We conduct an extensive set of experiments using a hundred hours of HUB4 data with ground truth transcript and twenty-four thousands query words. We show improvement of up to 15% in precision compare to results obtained speech recognition alone, at a processing time of 0.5 Sec per query.