Misako Imono

Judging Emotion from EEGs Based on an Association Mechanism

Abstract Authors focus on the emotion of which common sense and attempt to compose a method that judge the users emotion, based on EEGs. Emotion is judged from EEG features by an Association Mechanism. The Association Mechanism consists of the Concept Base and the Degree of Association. The methods of a Concept Base and a Degree of Association were proposed in the field of the natural language processing. In this paper, the research results are applied to EEGs. As a result, accuracy of emotion judgment from EEGs using the Association Mechanism was 57.6%. As a comparison, accuracy of emotion judgment at random was 25.0%, and accuracy of emotion judgment using SVM was 43.6%.

Method of Embodying the Meaning of Headlines Using News Articles

Abstract In recent years, various studies have investigated intelligent robots that can smoothly communicate with humans. Communication between humans is often achieved through conversation, so it is likely that robots will need to be able to perform human-like conversation. There are various types of human conversation. Intelligent robots will be expected to perform conversations a lot as human. In order to realize such conversation in robots, resourses for making new topics is required. We herein focus on the news website headlines because headlines are a more appropriate format for initiating conversation than the text of articles. However, there is a problem in that specific information is lacking from headlines. Therefore, this paper present a method of embodying the meaning of headlines using news articles for using headlines as a resource of the robot conversation. The proposed method embodies the meanings of news headlines by adding or replacing words in the headline with words from the articles. As a result, the proposed method was able to embody the meanings of Japanese headlines in a natural manner for approximately 58.3% of the 120 headlines belonging to the test set.

Automatic detection of illogical adjective phrase based on commonsense for computer conversation

This paper proposes a technique for judging illogical word combinations by creating a knowledge model of human discourse and words. We focused on a relation of nouns and adjective phrases. Then the knowledge structure of how to use nouns and adjective phrases is modeled by arranging the relation in a point of wrongness. Also, this paper proposes a technique for detection relation of nouns and adjective phrases by creating a knowledge model from generation of response sentences. This paper discusses detecting method illogical combinations of words. We showed that this technique was able to very accurately judge illogical usages with 87% accuracy, thus demonstrating the effectiveness of the technique.

A Simile Recognition System using a Commonsense Sensory Association Method

Abstract We propose a method for comprehending the significance of metaphorical expressions by using an intuitive sensory association method implemented on computer. The metaphors we address in this work are similes. When simile expressions are used in human conversation, it appears that the listener uses intuitive sensory associations, cultivated through experience, to recall the characteristics of the subject and the predicate and comprehend the meaning of the metaphor by replacing the predicate with another appropriate word to describe the subject. A sensory association method has been proposed that is capable of clarifying these sorts of intuitive sensory relationships between nouns and their characteristics. The sensory association method outputs the sensations and impressions that humans naturally feel in response to a given noun. In this work, we construct a simile comprehension system based on the sensory association method and seek to use it to get computers to understand similes. In this paper, we define comprehension of a simile—such as “cheeks like apples”—as to convert the simile into the phrase “red cheeks.” The capacity to perform this conversion demonstrates the computers understanding that the two expressions are synonymous. The results of our tests indicated an accuracy of 65.7%; thus, by introducing a sensory association method we were able to exceed the accuracy achieved in a previous study.

Method of Embodying the Newspaper Headlines by Using Words and Phrases in the Article

In recent years, various studies have investigated intelligent robots that can smoothly communicate with humans. Communication between humans is often achieved through conversation, so it is likely that robots will need to be able to perform human-like conversation. Intelligent robots will be expected to perform conversations a lot as human. In order to realize such conversation in robots, resourses for making new topics is required. This chapter herein focus on the news website headlines because headlines are a more appropriate format for initiating conversation than the text of articles. However, there is a problem in that specific information is lacking from headlines. Therefore, this chapter present a method of embodying the meaning of headlines using news articles for using headlines as a resource of the robot conversation. The proposed method embodies the meanings of news headlines by adding or replacing words in the headline with words from the articles.

Method for Suggesting Suitable Location-words for Demand Sentences☆

Abstract The ability to converse with human beings is essential if robots and humans are to communicate smoothly. Human responses are characterized by spontaneity, and conversational depth frequently veers between responses, suggestions, in-depth topic exploration, new topic introduction, and so on. Therefore, in this paper we propose a method of suggesting suitable location-words (words or short phrases representing locations) for demand sentences that can be applied to the technology responsible for ensuring smooth communication of humans and robots. Starting with a demand sentence, our proposed method creates a demand-concept from words that make up the demand sentence, after which a Web search is conducted to determine whether or not the obtained candidate location-words represent locations by using a thesaurus. Suitable location-words are then selected by calculating the DoA between location-word candidates and the demand-concept. In our evaluation of this concept, 86.7% of the location-words that were proposed by 60 demand sentences were determined to be correct.

Emotion judgment method from a meaning of an utterance sentence

Authors focus on the emotion of which common sense and attempt to compose a method that judge the users emotions based on utterances. Such system and method have already been developed. However, emotions might not be able to judge from the existing method accurately because of the polysemy of the word. In addition, a lot of resources are needed to make the existing method and to maintain a knowledge base. Therefore, a method is not processing in meaning categories of words separately, but translating an utterance sentence into a word is proposed in this paper. Herewith, both a polysemy problem and the maintenance problem of the knowledge base are solved. The proposed method uses knowledge base and an Association Mechanism. As a result, the accuracy of the proposed method was improved approximately 18.4% compare with an existing method.