Toshiyuki Takasaki

Language Grid Association: Action Research on Supporting the Multicultural Society

The Language Grid is a middleware with which people can connect and use language resources such as machine translations, morphological analyzers and others created in the fields of intercultural collaboration. The Language Grid cannot exist without the collaboration of Language Grid Users who provide language and computation resources, language services, and collaboration tools. This paper overviews Language Grid Association, a user group of the Language Grid and a body promoting action research to support the multicultural society.

Human detection of cultural differences in pictogram interpretations

Findings on how humans detect cultural differences in cross-cultural pictogram interpretations are reported. An open-answer web survey was conducted in the United States and Japan to collect U.S.-Japan pictogram interpretations. Thirty U.S.-Japan pictogram interpretations were used as stimuli for human cultural difference detection study. Three U.S. subjects and three Japanese subjects participated in the study to assess the degree of cultural differences in the thirty pictogram interpretations given in the questionnaire. Post-questionnaire interviews were conducted to elucidate the reasons behind the human cultural difference detection. The following factors were considered when humans detect cultural differences in cross-cultural pictogram interpretations: (i) similar or dissimilar interpretations in the two countries, (ii) percentage or ranking of the interpretations, (iii) conformity or variance of semantics within one countrys interpretations, (iv) presence of proper nouns (e.g. country names), and (v) positive or negative connotation in the interpretations.

Assisting pictogram selection with semantic interpretation

Participants at both end of the communication channel must share common pictogram interpretation to communicate. However, because pictogram interpretation can be ambiguous, pictogram communication can sometimes be difficult. To assist human task of selecting pictograms more likely to be interpreted as intended, we propose a semantic relevance measure which calculates how relevant a pictogram is to a given interpretation. The proposed measure uses pictogram interpretations and frequencies gathered from a web survey to define probability and similarity measurement of interpretation words. Moreover, the proposed measure is applied to categorized pictogram interpretations to enhance retrieval performance. Five pictogram categories are created using the five first level categories defined in the Concept Dictionary of EDR Electronic Dictionary. Retrieval performance among not-categorized interpretations, categorized and not-weighted interpretations, and categorized and weighted interpretations using semantic relevance measure were compared, and the categorized and weighted semantic relevance retrieval approach exhibited the highest F1 measure and recall.

Pictogram retrieval based on collective semantics

To retrieve pictograms having semantically ambiguous interpretations, we propose a semantic relevance measure which uses pictogram interpretation words collected from a web survey. The proposed measure uses ratio and similarity information contained in a set of pictogram interpretation words to (1) retrieve pictograms having implicit meaning but not explicit interpretation word and (2) rank pictograms sharing common interpretation word(s) according to query relevancy which reflects the interpretation ratio.

Multi-Language Discussion Platform for Wikipedia Translation

The multilingual Wikipedia is the largest existing collaboratively edited encyclopedia, where several translation communities are working towards translating Wikipedia articles. The different language communities are largely independent in terms of policy creation, behavior and community mechanisms. We conducted a case study on the Wikipedia community from a multilingual point of view to better understand community behavior. We also conducted a collaborative Wiki-to-Wiki translation experiment using machine translation tools provided by the Language Grid. Based on the findings of the two studies we designed and developed a multi-language discussion platform for Wikipedia translation communities. In this chapter, we discuss the results of the case study and a laboratory experiment and how the results are applied to facilitate the creation of multilingual collective intelligence in Wikipedia through a multi-language discussion platform.

Intercultural Communication Environment for Youth and Experts in Agriculture Support

There is ongoing research on information systems that support inter-disciplinary communication for people in different fields of expertise as well as on intercultural communication for people who speak different languages. However, there are few reports of research of systems that facilitate communication between youth and experts who speak different languages. In the presence of different languages and knowledge sets, a key issue lies in the implementing communication environments becomes difficult. This paper discusses a communication protocol designed to send/receive data and knowledge between youth and experts. This paper implements intercultural communication environment is implemented by combining machine translation services with human services to enhance communication quality. Finally, we validated the communication by applying the communication environment in agriculture support in Vietnam.

Youth Mediated Communication: Knowledge Transfer as Intercultural Communication

Transferring knowledge to other people in different languages is difficult because of gaps in languages and cultures. It makes the knowledge transfer more difficult when the recipient is young, because the comprehension and language ability of the young are incomplete. To better understand and design language services, this chapter introduces a communication protocol that meets requirements of agriculture support in rural areas, and fully delineates the communication environment by elucidating the field issues comprehensively; solutions are considered. The field experiment conducted involves agriculture support in Vietnam. In the context of agriculture support in rural areas, there exist several issues such as the requirement of timely knowledge transfer with high translation quality, and multilingual communication between youths and experts where gaps in language ability and expertise should be considered and addressed.

Supporting multilingual discussion for collaborative translation

In recent years, collaborative translation has become more and more important for translation volunteers to share knowledge among different languages, among which Wikipedia translation activity is a typical example. During the collaborative translation processes, users with different mother tongues always conduct frequent discussions about certain words or expressions to understand the content of original article and to decide the correct translation. To support such kind of multilingual discussions, we propose an approach to embedding a service-oriented multilingual infrastructure with discussion functions in collaborative translation systems, where discussions can be automatically translated into different languages with machine translators, dictionaries, and so on. Moreover, we propose a Meta Translation Algorithm to adapt the features of discussions for collaborative translation, where discussion articles always consist of expressions in different languages. Further, we implement the proposed approach on LiquidThreads, a BBS on Wikipedia, and apply it for multilingual discussion for Wikipedia translation to verify the effectiveness of this research.

Supporting a Children's Workshop with Machine Translation

Previous studies have investigated the characteristics of machine translation(MT)-mediated communication in lab settings and suggested various ways to improve it [1]. Unfortunately, we still lack an understanding of how MT is used in real-world settings, particularly when people use it to support face-to-face communication. In this paper, we report on a field study of a multilingual workshop where children from various language regions used MT to communicate with each other. We investigate how children use various information such as non-verbal cues and drawings to compensate for the mistranslations of MT. For example, children tried to understand the mistranslated messages by reading alternative translations and used web browsers to search for pictures of unknown objects. Such findings provide insights for designing future multilingual support systems.

Machine Translation Usage in a Children’s Workshop

Machine translation (MT) enables a group of people who do not share a common language to work together as a team. Previous studies have investigated the characteristics of MT-mediated communication in laboratory settings and suggested various ways to improve it. Yet, few studies have investigated how MT is actually used outside the lab. We still lack an understanding of how MT is used in real-world settings, particularly when people use it in face-to-face situations. In this paper, we report on an ethnographic study of a multilingual children workshop using MT to communicate with each other in real world. We studied how children use various communication methods such as gesture and internet to compensate for the mistranslations of MT. For example, children tried to understand poorly translated messages by reading the alternative translations and used web browsers to search for pictures of unknown objects. Finally, we propose design implementations based on our findings.