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

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.