• MALSORI
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• no.53
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• pp.171-183
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• 2005

Call Control eXtensible Markup (CCXML) is a standard language that supports a call control of voice dialog systems such as VoiceXML based systems. CCXML allows developers to handle telephony calls in an easy way without deep knowledge about telephony networks and their switching systems.We design and implement a call control markup interpreter. At the implementation, we use a Dialogic JCT-LS board, but, by designing a wrapping class for CTI (computer telephony board) features, the interpreter can easily adopt other CTI boards. We also design and implement event-based interaction scheme between the interpreter and voice dialog systems. For verifying the interaction scheme, we implement a simple voice dialog system.

• Journal of the HCI Society of Korea
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• v.12 no.1
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• pp.15-23
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• 2017

Applying the concept and components of human nature to the conversational agent in the smart home context, this study investigated the effects of the level of anthropomorphism and interaction type on the emotional user experiences and future use intention. The results of experiment study showed that the high-low condition of anthropomorphism and the voice-chatting interaction type have impacts on the perceived closeness, likability, and future use intention. That is, people evaluate the conversational agent as more close, likable, and useful when they perceive more human nature components and when in the voice interaction mode. Psychological resistance was lower in the voice than in the chatting mode regardless of the level of anthropomorphism. The results also demonstrated an interaction effect of anthropomorphism and interaction type on the future use intention: the effect of anthropomorphism existed only in the voice interaction mode. It leads to the conclusion that a conversational agent with the voice recognition interface should be designed with the higher level of human nature components for the continuous use.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.179-184
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• 2021

In this study, the conversation behavior of users is investigated by using in-vehicle voice interaction system. The purpose of this study is to identify the elements of conversations that the users expect in voice interactions with systems and present the structural improvements to enable the voice interactions similar to those between people. To observe the users' behavior of voice interaction in the vehicle, the data through contextual inquiry are collected and the interview contents are analyzed by using the open coding. We have been able to explore the usefulness of voice interaction features, which are of great importance in that they increase the user's satisfaction with the features and their usage persistence. This study is meaningful in analyzing the user's empirical needs for the technology of interpersonal model from the perspective of conversation.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.189-207
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• 2021

Voice interaction combined with artificial intelligence is poised to revolutionize human-computer interactions with the advent of virtual assistants. This paper is analyzing interactive elements of AI-based voice recognition services such as sympathy, assurance, intimacy, and trust on intention to use. The questionnaire was carried out for 284 smartphone/smart TV users in Korea. The collected data was analyzed by structural equation model analysis and bootstrapping. The key results are as follows. First, AI-based voice recognition service characteristics such as sympathy, assurance, intimacy, and trust have positive effects on interactivity with the AI-based voice recognition service. Second, the interactivity with the AI-based voice recognition service has positive effects on intention to use. Third, AI-based voice recognition service characteristics such as interactional enjoyment and intimacy have directly positive effects on intention to use. Fourth, AI-based voice recognition service characteristics such as sympathy, assurance, intimacy and trust have indirectly positive effects on intention to use the AI-based voice recognition service by mediating the effect of the interactivity with the AI-based voice recognition service. It is meaningful to investigate factors affecting the interactivity and intention to use voice recognition assistants. It has practical and academic implications.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.61-74
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• 2020

Voice user interface has become a commercially viable and extensive interaction mechanism with the development of voice assistants. Despite the popularity of voice assistants, the academic community does not utterly understand about what, when, and how users chat with them. Chatting with a voice assistant is crucial as it defines how a user will seek the help of the assistant in the future. This study aims to cover the essence and construct of conversational AI, to develop a classification method to deal with user utterances, and, most importantly, to understand about what, when, and how Chinese users chat with voice assistants. We collected user utterances from the real conventional database of a commercial voice assistant, NetEase Sing in China. We also identified different utterance categories on the basis of previous studies and real usage conditions and annotated the utterances with 17 labels. Furthermore, we found that the three top reasons for the usage of voice assistants in China are the following: (1) greeting, (2) function, and (3) music. Chinese users like to interact with voice assistants at night from 7 PM to 10 PM, and they are polite toward the assistants. The whole percentage of negative feedback utterances is less than 6%, which is considerably low. These findings appear to be useful in voice interaction designs for intelligent hardware.

• Journal of the HCI Society of Korea
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• v.11 no.2
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• pp.15-22
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• 2016

The ways to interact with digital appliances are becoming more diverse. Users can control appliances using a remote control and a touch-screen, and appliances can send users feedback through various ways such as sound, voice, and visual signals. However, there is little research on how to define which output method to use for providing feedback according to the user' input method. In this study, we designed an experimental study that seeks to identify how to appropriately match the output method - voice and sound - based on the user input - voice and button. We made four types of interaction with two kinds input methods and two kinds of output methods. For the four interaction types, we compared the usability, perceived satisfaction, preference and suitability. Results reveals that the output method affects the ease of use and perceived satisfaction of the input method. The voice input method with sound feedback was evaluated more satisfying than with the voice feedback. However, the keying input method with voice feedback was evaluated more satisfying than with sound feedback. The keying input method was more dependent on the output method than the voice input method. We also found that the feedback method of appliances determines the perceived appropriateness of the interaction.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.96-104
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• 2017

As new smart devices are evolved into the intelligent agent who can reflect user intention and use context, user experience design for easy and convenient usability becomes a core competitive edge. Under the assumption that human centered natural interaction is necessary for the optimal smart TV experience, this study explores the types of voice interaction which are peculiar to TV watching context. In order to build a model for the users to naturally interact with Smart TV, conversation patterns were collected by requesting key features of Smart TV to intelligent agent. Collected sentences were applied to CfA model and classified by responses to activate features. The classified conversation patterns were divided into feature activation and information search. This study has identified that CfC1 occurred when voice interaction between Smart TV and users was vague and CfC2 occurred when the requests were complex or conditional. In conclusion, Simple Request Type is the most efficient model and voice interaction is more appropriate to use to clarify users' vague requests.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.555-557
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• 1992

Recently, realization of an intelligent cooperative interaction system between a man and robot systems is required. In this paper, HyperCard with a voice control is used for above system because of its easy handling and excellent human interfaces. Clicking buttons in the HyperCard by a mouse device or a voice command means controlling each joint of a robot system. Robot teaching operation of grasping a bin and pouring liquid in it into a cup is carried out. This robot teaching method using HyperCard provides a foundation for realizing a user friendly cooperative interaction system.

• Journal of the Speleological Society of Korea
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• no.88
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• pp.1-7
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• 2008

Recently, it is one of very interest technology of Human Computer Interaction(HCI). Nowadays, it is easy to find out that, for example, inside SF movies people has talking to computer. However, there are difference between CPU language and ours. So, we focus on connecting to CPU. For 30 years many scientists experienced in that technology. But it is really difficult. Our project goal is making that CPU could understand human voice. First of all the signal through a voice sensor will move to BCD (binary code). That elevator helps out people who wants to move up and down. This product's point is related with people's safety. Using a PWM for motor control by ATmega16, we choose a DC motor to drive it because of making a regular speed elevator. Furthermore, using a voice identification module the elevator driven by voice sensor could operate well up and down perfectly from 1st to 10th floor by PWM control with ATmega16. And, it will be clearly useful for high-rise vertical shift with voice recognition sensor driven.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1156-1166
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• 2022

In this study, we examined voice shopping interaction in which consumers can be involved in the decision-making process. Sixteen kinds of voice shopping interaction were designed with differences in the existence of screen/product involvement/conversation style. Their effects on trust, cognitive load, satisfaction, and continuous intention to use were evaluated through a survey experiment. The main effect of conversation style was significant, and it was found that the more deeply involved users have higher trust. The interaction effect between conversation style and product involvement was also significant. Low involvement product buyers had the most positive user experience from the conversation style that included 'Ask for preference,' while high involvement product buyers had the most positive user experience from the conversation style that included both 'Ask for preference' and 'Question and Answer.' The main effect and interaction effect of the existence of screen was not significant. The results indicate that a positive user experience can be obtained when users are deeply involved in consumer decision-making, especially in purchasing high-involvement products.