Frequently interrupting someone who is busy will decrease his or her productivity. To minimize this risk, a number of interruptibility estimation methods based on PC activity such as typing or mouse clicks have been developed. However, these estimation methods do not take account of the effect of conversations in relation to the interruptibility of office workers engaged in intellectual activities such as scientific research. This study proposes an interruptibility estimation method that takes account of the conversation status. Two conversation indices, “In conversation” and “End of conversation” were used in a method that we developed based on our analysis of 50 hours worth of recorded activity. Experiments, using the conversation status as judged by the Wizard-of-OZ method, demonstrated that the estimation accuracy can be improved by the two indices. Furthermore, an automatic conversation status recognition system was developed to replace the Wizard-of-OZ procedure. The results of using it for interruptibility estimation suggest the effectiveness of the automatically recognized conversation status.

In order not to disrupt a team member concentrating on his/her own task, the interrupter needs to wait for a proper time. In this research, we examined the feasibility of predicting prospective interruptible times of office workers who use PCs. An analysis of actual working data collected from 13 participants revealed the relationship between uninterruptible durations and four features, i.e. type of application software, rate of PC operation activity, activity ratio between keystrokes and mouse clicks, and switching frequency of application software. On the basis of these results, we developed a probabilistic work continuance model whose probability changes according to the four features. The leave-one-out cross-validation indicated positive correlations between the actual and the predicted durations. The medians of the actual and the predicted durations were 539 s and 519 s. The main contribution of this study is the demonstration of the feasibility to predict uninterruptible durations in an actual working scenario.

This study discusses the feasibility to estimate the concentration level of Japanese document workers using computer. Based on the previous findings that dual-task scenarios increase reaction time, we hypothesized that the Kana-Kanji conversion confirmation time (KKCCT) would increase due to the decrease in cognitive resources allocated to the document task, i.e. the level of concentration on the task at hand. To examine this hypothesis, we conducted a set of experiments in which sixteen participants copied Kana text by typing and concurrently converted it into Kanji under three conditions: Normal, Dual-task, and Mental-fatigue. The results suggested the feasibility that KKCCT increased when participants were less concentrated on the task due to subtask or mental fatigue. These findings imply the potential utility of using confirmation time as a measure of concentration level in Japanese document workers.

Aimed at long-term monitoring of daily office conversations without recording the conversational content, a system is presented for estimating acoustic nonverbal information such as utterance duration, utterance frequency, and turn-taking. The system combines a sound localization technique based on the sound energy distribution with 16 beam-forming microphone-array modules mounted in the ceiling for reducing the influence of multiple sound reflection. Furthermore, human detection using a wide field of view camera is integrated to the system for more robust speaker estimation. The system estimates the speaker for each utterance and calculates nonverbal information based on it. An evaluation analyzing data collected over ten 12-hour workdays in an office with three assigned workers showed that the system had 72% speech segmentation detection accuracy and 86% speaker identification accuracy when utterances were correctly detected. Even with false voice detection and incorrect speaker identification and even in cases where the participants frequently made noise or where seven participants had gathered together for a discussion, the order of the amount of calculated acoustic nonverbal information uttered by the participants coincided with that based on human-coded acoustic nonverbal information. Continuous analysis of communication dynamics such as dominance and conversation participation roles through nonverbal information will reveal the dynamics of a group. The main contribution of this study is to demonstrate the feasibility of unconstrained long-term monitoring of daily office activity through acoustic nonverbal information.

Various systems that share remote co-worker's awareness information have been proposed for realizing efficient collaborative work among distributed offices. In this study, we implemented an interruptibility sharing system in a university laboratory and assessed the observation behavior for the displayed information. Observation behavior for each target member was detected using an eye tracker to discuss the usage and effect of the system in a quantitative manner, along with the considerations of workers' job positions and relationships. The results suggested that participants observed interruptibility information approximately once an hour while at their desks. Observations were frequent during break-times rather than when the participants wanted to communicate with others. The most frequently observed targets were the participants themselves. The participants gazed the laboratory members not only in a close work relationship but also in a weak relationship. Results suggested that sharing of interruptibility information assists worker's self-reflection and contributes to the establishment of horizontal connection in an organization including members in weak work relationship.