Many studies of on-line comprehension of semantic violations have shown that the human sentence processor rapidly constructs a higher-order semantic interpretation of the sentence. What remains unclear, however, is the amount of time required to detect semantic anomalies while concatenating two words to form a phrase with very rapid stimuli presentation. We aimed to examine the time course of semantic integration in concatenating two words in phrase structure building, using magnetoencephalography (MEG). In the MEG experiment, subjects decided whether two words (a classifier and its corresponding noun), presented each for 66 ms, form a semantically correct noun phrase. Half of the stimuli were matched pairs of classifiers and nouns. The other half were mismatched pairs of classifiers and nouns. In the analysis of MEG data, there were three primary peaks found at approximately 25 ms (M1), 170 ms (M2) and 250 ms (M3) after the presentation of the target words. As a result, only the M3 latencies were significantly affected by the stimulus conditions. Thus, the present results indicate that the semantic integration in concatenating two words starts from approximately 250 ms.

This paper describes automatic generation of speech synthesis rules which predict a stress level for each bunsetsu in long noun phrases. The rules are inductively inferred from a lot of speech data by using two kinds of tree-based methods, the conventional decision tree and the SBR-tree methods. The rule sets automatically generated by two methods have almost the same performance and decrease the prediction error to about 14 Hz from 23 Hz of the accent component value. The rate of the correct reproduction of the change for adjacent bunsetsu pairs is also used as a measure for evaluating the generated rule sets and they correctly reproduce the change of about 80%. The effectiveness of the rule sets is verified through the listening test. And, with regard to the comprehensiveness of the generated rules, the rules by the SBR-tree methods are very compact and easy to human experts to interpret and matches the former studies.