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Pronunciation Variation Modeling for Korean Point-of-Interest Data Using Prosodic Information  

Kim, Sun-He (서울대학교 인문정보연구소)
Park, Jeon-Gue (한국전자통신연구원)
Na, Min-Soo (서울대학교 인지과학협동과정)
Jeon, Je-Hun (서강대학교 컴퓨터학과)
Chung, Min-Wha (서울대학교 언어학과)
Publication Information
Journal of KIISE:Software and Applications / v.34, no.2, 2007 , pp. 104-111 More about this Journal
Abstract
This paper examines how the performance of an automatic speech recognizer was improved for Korean Point-of-Interest (POI) data by modeling pronunciation variation using structural prosodic information such as prosodic words and syllable length. First, multiple pronunciation variants are generated using prosodic words given that each POI word can be broken down into prosodic words. And the cross-prosodic-word variations were modeled considering the syllable length of word. A total of 81 experiments were conducted using 9 test sets (3 baseline and 6 proposed) on 9 trained sets (3 baseline, 6 proposed). The results show: (i) the performance was improved when the pronunciation lexica were generated using prosodic words; (ii) the best performance was achieved when the maximum number of variants was constrained to 3 based on the syllable length; and (iii) compared to the baseline word error rate (WER) of 4.63%, a maximum of 8.4% in WER reduction was achieved when both prosodic words and syllable length were considered.
Keywords
Pronunciation modeling; Pronunciation variation; Prosodic word; Syllable; Point-of-Interest data;
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