سال انتشار: ۱۳۹۰
محل انتشار: همایش ملی کامپیوتر و فناوری اطلاعات
تعداد صفحات: ۵
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
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.