Ari Hautasaari

Lost in transmittance: how transmission lag enhances and deteriorates multilingual collaboration

Previous research has shown that audio communication is particularly difficult for non-native speakers (NNS) during multilingual collaborations. Especially when audio signals become distorted, NNS are overburdened by not only having to communicate with imperfect language skills, but also compensating for the deteriorations. Under these faulty audio conditions, NNS need to pay extra time and effort to understand the conversation. In order to give NNS more time to process conversations, we tested the insertion of silent gaps (from 0.2 to 0.4 seconds) between conversational turns. First, gaps were inserted into a previously taped conversation, resulting in a significant improvement of NNSs understanding of the conversation. Second, gaps were inserted during a real-time audio conference by adding artificial delay between native speakers. The results show that the added delays have a combination of beneficial and detrimental effects for both native and non-native speakers. The findings have implications towards how audio conferencing can be improved for NNS.

Analysis of discussion contributions in translated Wikipedia articles

Translation of articles in Wikipedia is one of the most prominent methods for increasing the quality of different language Wikipedias. Discussion pages in Wikipedia contribute to a large portion of the online encyclopedia, and are used by Wikipedia contributors for communication and collaboration. Although the discussion pages are the main channel between Wikipedia contributors all over the world, there have been relatively few in-depth studies conducted on communication in Wikipedia, especially regarding translation activities. This paper reports the results of an analysis of discussions about translated articles in the Finnish, French and Japanese Wikipedias. The results highlight the main problems in Wikipedia translation requiring interaction with the community. Unlike in previous work, community interaction in Wikipedia translation activities focuses on solving problems in the translation of proper nouns, transliteration and citing sources in articles rather than mechanical translation of words and sentences. Based on these findings we propose directions for designing supporting tools for Wikipedia translators.

Machine translation effects on group interaction: an intercultural collaboration experiment

Even with the increasing use of machine translation to overcome language barriers it is still unclear how machine translation affects communication and interaction in intercultural groups. In this paper, we present the results of a laboratory experiment on intercultural distributed groups using machine translation-mediated chat as a communication tool. English-speaking participants from Finland and Japan worked with Japanese-speaking participants in a trading game scenario using machine translation-mediated chat as their main communication tool. Based on previous research we predicted that machine translation will help overcome the language barrier, but furthermore we predicted that machine translation would have a positive effect on social and relational communication as well as on overall group performance. In a controlled laboratory setting, machine translation proved to increase the amount of positive socioemotional messages and overall group performance in intercultural distributed groups with disparate language abilities.

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.

Discussion about Translation in Wikipedia

Discussion pages in individual Wikipedia articles are a channel for communication and collaboration between Wikipedia contributors. Although discussion pages contribute to a large portion of the online encyclopedia, there have been relatively few in-depth studies conducted on the type of communication and collaboration in the multilingual Wikipedia, especially regarding translation activities. This paper reports the results on an analysis of discussion about translation in the Finnish, French and Japanese Wikipedias. The analysis results highlight the main problems in Wikipedia translation requiring interaction with the community. Unlike reported in previous works, community interaction in Wikipedia translation focuses on solving problems in source referencing, proper nouns and transliteration in articles, rather than mechanical translation of words and sentences. Based on these findings we propose future directions for supporting translation activities in Wikipedia.

How Non-Native English Speakers Perceive the Emotional Valence of Messages in Text-Based Computer-Mediated Communication

ABSTRACT We explore how native and non-native English speakers interpret cues of emotional expression in native English speakers, text-only messages in two studies. In Experiment 1, 28 native English speakers and 28 Japanese non-native English speakers rated the emotional valence of 98 public Facebook status updates written by native English-speaking authors. We found that non-native speakers were less accurate at detecting the emotional valence and perceived messages more neutral or intensely negative than native speakers. In Experiment 2 we found that non-native speakers’ cultural background and lack of confidence in second-language ability may influence how they adjust their perceptions on a message based on subsequent replies. Our results contribute to theoretical development in multilingual socioemotional communication in computer-mediated environments and have implications for design of technologies to support socioemotional text-based communication between native and non-native speakers.

Could someone please translate this?: activity analysis of wikipedia article translation by non-experts

Wikipedia translation activities aim to improve the quality of the multilingual Wikipedia through article translation. We performed an activity analysis of the translation work done by individual English to Chinese non-expert translators, who translated linguistically complex Wikipedia articles in a laboratory setting. From the analysis, which was based on Activity Theory, and which examined both information search and translation activities, we derived three translation strategies that were used to inform the design of a support system for human translation activities in Wikipedia.

Emotion Detection in Non-native English Speakers’ Text-Only Messages by Native and Non-native Speakers

When people from different language backgrounds communicate, they need to adopt a common shared language, such as English, to set up the conversation. In conversations conducted over text-only computer-mediated communication (CMC) mediums, mutual exchange of socio-emotional information is limited to the use of words, symbols and emoticons. Previous research suggests that when message receivers share the same native language with the authors, they are more accurate at detecting the emotional valence of messages based on these cues compared to non-native speaking receivers. But is this still true when the messages are written by non-native speakers? Moreover, what message properties influence the accuracy of emotional valence detection? In this paper, we report on an experiment where native English speakers and Japanese non-native English speakers rate the emotional valence of text-only messages written by Japanese non-native English speaking authors. We analyze how three message properties, grammatical correctness, fluency of language and use of symbols and emoticons, influence emotional valence detection for native and non-native speakers. Based on our results, we propose theoretical and practical implications for supporting multilingual socio-emotional communication in text-only CMC.

Intercultural collaboration with the language grid toolbox

In this demonstration video, we introduce the Language Grid Toolbox, an open source multilingual communication tool, and two community sites based on the Language Grid Toolbox. The G30 Community Site aims to create a multilingual and multicultural community to accommodate the needs of Japanese and international students. The Pangaea Community Site is used by facilitators of NPO Pangaea located in different countries around the world to communicate in their native languages through machine translation supported multilingual BBS.