NDLI: A distinctive feature based method for evaluating the phonetic transcription of a non-native speech database

Content Provider	IEEE Xplore Digital Library
Author	Jinsong Zhang Dongning Wang Wen Cao Ziyu Xiong
Copyright Year	2010
Description	Author affiliation: Center of Studies of Chinese as a Second Language, Beijing Language and Culture University, China (Jinsong Zhang; Dongning Wang; Wen Cao) \|\| Institute of Linguistics, Chinese Academy of Social Sciences, Beijing, China (Ziyu Xiong)
Abstract	For the purpose of studies of second language acquisition and computer aided pronunciation training, an L2 Chinese speech database by Japanese learners has been collected and phonetically annotated twice by two independent groups of labelers. As there are errors in the two annotations, appropriate methods are needed to screen out inconsistencies for rechecking. This paper presents a multi-step procedure to deal with the problem: first screen out checking candidates based on statistical distributional analyses of inconsistent transcriptions, then analyze and merge inconsistent phoneme transcriptions based on phonetic knowledge, finally make use of a phonetic feature based analyzer to order those inconsistent pair labels for rechecking. Those labels with most dissimilarity are assigned with top priority for rechecking. Preliminary experimental results showed that the procedure was helpful to generate a meaningful candidate list and priority ordering for rechecking.
Starting Page	416
Ending Page	419
File Size	159020
Page Count	4
File Format	PDF
ISBN	9781424462445
e-ISBN	9781424462469
DOI	10.1109/ISCSLP.2010.5684857
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-29
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	inter-language database Tongue Correlation Databases distinctive features Speech Reliability Labeling Compounds inter-labeler agreement
Content Type	Text
Resource Type	Article

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