Yasutomo Kimura

Evaluation of Japanese Dialogue Processing Method Based on Similarity Measure Using tf· AoI

In this paper, we propose a Japanese dialogue processing method based on a similarity measure using tf· AoI(termfrequency × Amountof Information). Keywords are specially used in a spoken dialogue system because a user utterance includes an erroneous recognition, filler and a noise. However, when a system uses keywords for robustness, it is difficult to realize detailed differences. Therefore, our method calculates similarity between two sentences without deleting any word from an input sentence, and we use a weight which multiplies term frequency and amount of information(tf · AoI). We use 173 open data sets which are collected from 12,095 sentences in SLDB. The experimental result using our method has a correct response rate of 67.1%. We confirmed that correct response rate of our method was 11.6 points higher than that of the matching rate measure between an input sentence and a comparison sentence. Furthermore that of our method was 7.0 points higher than that of tf · idf.

A Web-Based Visualization System for Interdisciplinary Research Using Japanese Local Political Corpus

This paper describes a web-based visualization system, for interdisciplinary research, using the Japanese local political corpus. We illustrate the system for the corpus, which contains the local assembly minutes of 47 Japanese prefectures from April 2011 to March 2015. This four-year period coincides with the office term for assembly members in most local governments. Our system provides full-text search features for utterances, context word extraction using Key Words in Context (KWIC), map visualization, cross-tabulation tables, and political keyword extraction using TF–IDF. We endowed the system with these features to promote its wide range use in various research fields.

Automatic Extraction of Harmful Sentence Patterns with Application in Cyberbullying Detection.

The problem of humiliating and slandering people through Internet, generally defined as cyberbullying (later: CB), has been recently noticed as a serious social problem disturbing mental health of Internet users. In Japan, to deal with the problem, members of Parent-Teacher Association (PTA) perform Internet Patrol – a voluntary work by reading through the whole Web contents to spot cyberbullying entries. To help PTA members we propose a novel method for automatic detection of malicious contents on the Internet. The method is based on a brute force search algorithm-inspired combinatorial approach to language modeling. The method automatically extracts sophisticated sentence patterns and uses them in classification. We tested the method on actual data containing cyberbullying provided by Human Rights Center. The results show our method outperformed previous methods. It is also more efficient as it requires minimal human effort.

Onomatopoeias in the Corpus of Japanese Regional Assembly Minutes: Analysis of the Appearance Tendency and the Word Sense@@@出現傾向と語義の分析

An onomatopoeia is a useful linguistic expression to describe sounds, conditions, degrees and so on. It is said Japanese is rich in onomatopoeic expressions. They are frequently used in daily conversations. The meaning and surface structure of an onomatopoeia varies diachronically. There seem to be regional variations in usage of onomatopoeias. It is necessary to investigate the actual condition of onomatopoeia quantitatively in order to apply onomatopoeias into artificial intelligence. This paper studies practical usages of onomatopoeias in spoken modern Japanese language. To explore Japanese onomatopoeias nowadays, we investigate regional assembly minutes collected from all areas in Japan. The corpus of regional assembly minutes, which has about 300 million words, is the target of the investigation of this study. The minutes of Japanese regional assemblies contain all transcriptions of the utterances in the assemblies. This corpus is suitable for our research since attributes of the speakers are clear and speakers are distributed nation-wide. The first research is about total frequency and regional distribution of onomatopoeias. The onomatopoeias, which represent a request for a promotion of policy, e.g., “shikkari”, “dondon”, are used at high frequency in regional assemblies. There are no remarkable regional differences in frequencies of these onomatopoeias though western Japan has slight higher frequency. The second research is about the meaning of the onomatopoeias. Most of onomatopoeias are polysemous. The meaning of the onomatopoeia differs by context. The authors have manually checked through 10,827 sentences, which contain 153 kinds of onomatopoeia, and then classified the meaning of each onomatopoeic expression. We analyzed for the following subjects: i) ambiguity of onomatopoeic expression, ii) regional differences in meaning, iii) new meanings in modern spoken language, iv) special usage in assemblies, and v) onomatopoeias in the named entities. The third research is about false extraction of onomatopoeias in the morphological analysis. The extraction errors are analyzed from the viewpoint of surface structure and appearance position. In terms of surface structure, it is clear that the word length of an onomatopoeic expression, which has highly false extraction, is shorter. The onomatopoeic expressions, which end with special morae, namely moraic obstruent, moraic nasal and long vowel, have a higher rate of false extraction. In terms of appearance position, dialectal grammar is the main factor causing false extraction. About 25% of false extraction is found in the sentence-closing particles in dialectal grammar. The result of quantitative analysis of the onomatopoeia in modern spoken Japanese language serves as the basic data which contributes to engineering. The results of the analysis in our research are exhibited through the WWW. It is hoped that results will contribute broadly to the practical use of onomatopoeia in the engineering field.

Proposal of Precedents Processing System for Supporting Japanese Lay Judges

We propose law professionals and amateurs supporting system for upcoming ¿lay judge system¿. The supporting system finds past cases which are similar to a target case and estimates a sentence of target case. After describing the need of such project, we carry out an preliminary experiment to extract similar judicial precedents and estimate a sentence based on features of noun words. Then we introduce our preliminary findings and possibility of tagging and using so called Nagayama criteria used by human judges.