Waiting is an indispensable and inevitable part of man-machine voice interaction. The voice user interface (VUI) feedback mechanism is a key factor affecting voice interaction's waiting experience. The feedback time of most available voice interfaces is fixed or decided by the processing time of hardware and software, which has not been designed and cannot offer users a good interaction experience. In this paper, the speech rate of user-machine voice interaction is collected through prototype experimentation. Besides, users' time perception of different voice interfaces' feedback time settings is studied based on time psychology theories. Moreover, users' emotional changes are described after a specific feedback time with the distribution of two-dimension arousal-valence emotion space. Users' time perception and subjective emotions are differently influenced by different VUI feedback times. The experimental results show that 750 ms is the optimal VUI feedback time point at which the best users' subjective feelings and psychological experiences are reached, and the threshold limit time spent by users in waiting for the VUI feedback is 1,850 ms which will lead to user emotions with low levels of arousal and valence after being exceeded. Based on that, a linear regression model is proposed to define the optimal feedback time of VUI. The user experience VUI research results show that the calculated feedback time parameters can make users produce time perception in line with their expectations in interacting with voice interfaces.INDEX TERMS Voice user interface, feedback time, time perception, speech rate.

Voice user interface (VUI) is widely used in developing intelligent products due to its low learning cost. However, most of such products do not consider the cognitive and language ability of elderly people, which leads to low interaction efficiency, poor user experience, and unfriendliness to them. Firstly, the paper analyzes the factors which influence the voice interaction behavior of elderly people: speech rate of elderly people, dialog task type, and feedback word count. And then, the voice interaction simulation experiment was designed based on the wizard of Oz testing method. Thirty subjects (M = 61.86 years old, SD = 7.16; 15 males and 15 females) were invited to interact with the prototype of a voice robot through three kinds of dialog tasks and six configurations of the feedback speech rate. Elderly people’s speech rates at which they speak to a person and to a voice robot, the feedback speech rates they expected for three dialog tasks were collected. The correlation between subjects’ speech rate and the expected feedback speech rate, the influence of dialog task type, and feedback word count on elderly people’s expected feedback speech rate were analyzed. The results show that elderly people speak to a voice robot with a lower speech rate than they speak to a person, and they expected the robot feedback speech rate to be lower than the rate they speak to the robot. There is a positive correlation between subjects’ speech rate and the expected speech rate, which implies that elderly people with faster speech rates expected a faster feedback speech rate. There is no significant difference between the elderly people’s expected speech rate for non-goal-oriented and goal-oriented dialog tasks. Meanwhile, a negative correlation between the feedback word count and the expected feedback speech rate is found. This study extends the knowledge boundaries of VUI design by investigating the influencing factors of voice interaction between elderly people and VUI. These results also provide practical implications for developing suitable VUI for elderly people, especially for regulating the feedback speech rate of VUI.