Certain irregularities in the utterances of words or phrases often occur in English spoken by Japanese native subject, referred to in this article as Japanese English. Japanese English is linguistically presumed to reflect the phonetic characteristics of Japanese. We consider the prosodic feature patterns as one of the most common causes of irregularities in Japanese English, and that Japanese English would have better prosodic patterns if its particular characteristics were modified. This study investigates prosodic differences between Japanese English and English speakers' English, and shows the quantitative results of a statistical analysis of pitch. The analysis leads to rules that show how to modify Japanese English to have pitch patterns closer to those of English speakers. On the basis of these rules, the pitch patterns of test speech samples of Japanese English are modified, and then re-synthesized. The modified speech is evaluated in a listening experiment by native English subjects. The result of the experiment shows that on average, over three-fold of the English subjects support the proposed modification against original speech. Therefore, the results of the experiments indicate practical verification of validity of the rules. Additionally, the results suggest that irregularities of prominence lie in Japanese English sentences. This can be explained by the prosodic transfer of first language prosodic characteristics on second language prosodic patterns.

In this paper, we propose a statistical model for detecting article errors, which Japanese learners of English often make in English writing. It is based on the three head words--the verb head, the preposition, and the noun head. To overcome the data sparseness problem, we apply the backed-off estimate to it. Experiments show that its performance (F-measure=0.70) is better than that of other methods. Apart from the performance, it has two advantages: (i) Rules for detecting article errors are automatically generated as conditional probabilities once a corpus is given; (ii) Its recall and precision rates are adjustable.