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Selective Attention Measurement of Experienced Simultaneous Interpreters Using EEG Phase-Locked Response
We quantified the electroencephalogram signals associated with the selective attention processing of experienced simultaneous interpreters and calculated the phase-locked responses evoked by a 40-Hz auditory steady-state response (40-Hz ASSR) and the values of robust inter-trial coherence (ITC) for environmental changes. Since we assumed that an interpreter's attention ability improves with an increase in the number of years of experience of simultaneous interpretation, we divided the participants into two groups based on their simultaneous interpretation experience: experts with more than 15 years of experience (E group; n = 7) and beginners with <1 year (B group; n = 15). We also compared two conditions: simultaneous interpretation (SI) and shadowing (SH). We found a significant interaction in the ITC between years of SI experience (E and B groups) and tasks (SI and SH). This result demonstrates that the number of years of SI experience influences selective attention during interpretation.journal articl
Report on 2020 International Conference on Emerging Technologies for Communications (ICETC 2020)
The IEICE Communications Society hosted the 2020 International Conference on Emerging Technologies for Communications (hereinafter referred to as “ICETC2020”) online from December 2-4, 2020 [1].Figures 1 and 2 present opening ceremony on Dec. 2 and reception on Dec. 4, respectively.This conference was the first flagship international conference organized by a Society in IEICE. The conference was attended by 589 participants including many students.journal articl
Virtual Reality as a Reflection Technique for Public Speaking Training
Video recording is one of the most commonly used techniques for reflection, because video allows people to know what they look like to others and how they could improve their performance, but it is problematic because some people easily fall into negative emotions and worry about their performance, resulting in a low benefit. In this study, the possibility of applying a simple VR-based reflection method was explored. This method uses virtual reality (VR) and a head-mounted display (HMD) to allow presenters to watch their own presentations from the audience’s perspective and uses an avatar, which hides personal appearance, which has low relevance to the quality of presentation, to help reduce self-awareness during reflection. An experimental study was carried out, considering four personal characteristics?gender, personal anxiety, personal confidence and self-bias. The goal of this study is to discuss which populations can benefit more from this system and to assess the impact of the avatar and HMD-based VR. According to the results, the individuals with low self-confidence in their public speaking skills could benefit more on self-evaluation from VR reflection with HMD, while individuals with negative self-bias could reduce more anxiety by using an avatar.journal articl
Semantic Textual Similarity in Japanese Clinical Domain Texts Using BERT
Background?Semantic textual similarity (STS) captures the degree of semantic similarity between texts. It plays an important role in many natural language processing applications such as text summarization, question answering, machine translation, information retrieval, dialog systems, plagiarism detection, and query ranking. STS has been widely studied in the general English domain. However, there exists few resources for STS tasks in the clinical domain and in languages other than English, such as Japanese.Objective?The objective of this study is to capture semantic similarity between Japanese clinical texts (Japanese clinical STS) by creating a Japanese dataset that is publicly available.Materials?We created two datasets for Japanese clinical STS: (1) Japanese case reports (CR dataset) and (2) Japanese electronic medical records (EMR dataset). The CR dataset was created from publicly available case reports extracted from the CiNii database. The EMR dataset was created from Japanese electronic medical records.Methods?We used an approach based on bidirectional encoder representations from transformers (BERT) to capture the semantic similarity between the clinical domain texts. BERT is a popular approach for transfer learning and has been proven to be effective in achieving high accuracy for small datasets. We implemented two Japanese pretrained BERT models: a general Japanese BERT and a clinical Japanese BERT. The general Japanese BERT is pretrained on Japanese Wikipedia texts while the clinical Japanese BERT is pretrained on Japanese clinical texts.Results?The BERT models performed well in capturing semantic similarity in our datasets. The general Japanese BERT outperformed the clinical Japanese BERT and achieved a high correlation with human score (0.904 in the CR dataset and 0.875 in the EMR dataset). It was unexpected that the general Japanese BERT outperformed the clinical Japanese BERT on clinical domain dataset. This could be due to the fact that the general Japanese BERT is pretrained on a wide range of texts compared with the clinical Japanese BERT.journal articl
Effects of Augmented Reality Object and Texture Presentation on Walking Behavior
Wearable devices that display visual augmented reality (AR) are now on the market, and we are becoming able to see AR displays on a daily basis. By being able to use AR displays in everyday environments, we can benefit from the ability to display AR objects in places where it has been difficult to place signs, to change the content of the display according to the user or time of day, and to display video. However, there has not been sufficient research on AR displays’ effect on users in everyday environments. In this study, we investigate how users are affected by AR displays. In this paper, we report our research results on the AR displays’ effect on the user’s walking behavior. We conducted two types of experiments?one on the effects of displaying AR objects on the user’s walking path, and the other on the effects of changing the floor texture by AR on the user’s walking behavior. As a result of the experiments, we found that the AR objects/textures affected the user’s walking behavior.journal articl
A Study on Persistence of GAN-Based Vision-Induced Gustatory Manipulation
Vision-induced gustatory manipulation interfaces can help people with dietary restrictions feel as if they are eating what they want by modulating the appearance of the alternative foods they are eating in reality. However, it is still unclear whether vision-induced gustatory change persists beyond a single bite, how the sensation changes over time, and how it varies among individuals from different cultural backgrounds. The present paper reports on a user study conducted to answer these questions using a generative adversarial network (GAN)-based real-time image-to-image translation system. In the user study, 16 participants were presented somen noodles or steamed rice through a video see-through head mounted display (HMD) both in two conditions; without or with visual modulation (somen noodles and steamed rice were translated into ramen noodles and curry and rice, respectively), and brought food to the mouth and tasted it five times with an interval of two minutes. The results of the experiments revealed that vision-induced gustatory manipulation is persistent in many participants. Their persistent gustatory changes are divided into three groups: those in which the intensity of the gustatory change gradually increased, those in which it gradually decreased, and those in which it did not fluctuate, each with about the same number of participants. Although the generalizability is limited due to the small population, it was also found that non-Japanese and male participants tended to perceive stronger gustatory manipulation compared to Japanese and female participants. We believe that our study deepens our understanding and insight into vision-induced gustatory manipulation and encourages further investigation.journal articl