Publikationen

A lot of people in Japan suffer from bad conditions of their mental health with an increasing tendency, in particular jobseekers and elderly persons. The classical way to solve their problem is to consult a counselor, who treats these people in a way to become aware of the core of their problem and to solve it. However, the number of well qualified counselors is limited. For this purpose, we developed a VCA (Virtual Counseling Agent) as a further evolution of a formerly developed CRECA (Context Respectful Counseling Agent). CRECA. CRECA had a text interface. To much more imitate a human counselor, VCA has an image avatar and a voice conversation using the Google Cloud audio API. Further, VCA is made independent of counseling content fields. Thus, it is more generalized than CRECA or ELIZA in order for every people to easily use everywhere in every situation. Here, VCA, CRECA, and ELIZA are comparatively evaluated by questionnaire after the use of 10 college students having career problems as well as elderly persons struggling with modern IT. As a result, VCA significantly exceeded the average value of ELIZA along with the significant difference at the level of 5%. Moreover, average of the evaluation value is not worse than CRECA. Compared to CRECA, VCA does not limit the content and field of consultation. Especially, elderly persons struggling with modern IT could not use CRECA that have only text interface. It can be used generally at any time in everyday natural conversation. It can easily be used by elderly people and the digital divided due to voice conversion.

We present VICA, a Visual Counseling Agent designed to create an engaging multimedia face-to-face interaction. VICA is a human-friendly agent equipped with high performance voice conversation designed to help psychologically stressed users, to offload their emotional burden. Such users specifically include non-computer-savvy elderly persons or clients. Our agent builds replies exploiting interlocutor's utterances expressing such as wishes, obstacles, emotions, etc. Statements asking for confirmation, details, emotional summary, or relations among such expressions are added to the utterances. We claim that VICA is suitable for positive counseling scenarios where multimedia specifically high-performance voice communication is instrumental for even the old or digital divided users to continue dialogue towards their self-awareness. To prove this claim, VICA's effect is evaluated with respect to a previous text-based counseling agent CRECA and ELIZA including its successors. An experiment involving 14 subjects shows VICA effects as follows: (i) the dialogue continuation (CPS: Conversation-turns Per Session) of VICA for the older half (age > 40) substantially improved 53% to CRECA and 71% to ELIZA. (ii) VICA's capability to foster peace of mind and other positive feelings was assessed with a very high score of 5 or 6 mostly, out of 7 stages of the Likert scale, again by the older. Compared on average, such capability of VICA for the older is 5.14 while CRECA (all subjects are young students, age < 25) is 4.50, ELIZA is 3.50, and the best of ELIZA's successors for the older (> 25) is 4.41.

A lot of IT personnel have psychological distress and counselors to help them are lack in number. Therefore, we proposed a counseling agent (CA) called CRECA (context respectful counseling agent), which listens to clients and promotes their reflection context respectfully namely in a context preserving way. This agent is now enhanced using a body language called "unazuki" in Japanese, a kind of nodding to greatly promote dialogue, often accompanying "un-un" (meaning "exactly") of Japanese onomatopoeia. This body language significantly helps represent empathy or entire approval. Our agent is enhanced with such dialog promotion nodding robot to continue the conversation naturally or context respectfully towards clients' further reflection. To realize it, the robot nods twice at each end of dialog sentence input by clients. Here, we introduce a robot that behaves human-like by an appropriate nodding behavior. The motivation for such a more human-like robot was the extension of application fields from IT workers' counselling to people, who suffer from more social problems such as financial debt, or anxiety of victory or defeat. For such applications, it is important that the agent behaves as much as possible human-like. Here, we present an enhanced experimental evaluation. The quantitative evaluation is based on the utterance amounts of a test group of individuals. These amount with and without the nodding feature are compared. Additionally, the robots with and without nodding are compared according several subjective feelings by the evaluation subjects.

There are significantly many people including IT workers, old persons, job seekers, etc., who suffer from (psychological) distress in their work or life. Compared with this, there are only a limited number of human counselors who can provide mental care to such many distress persons. Initially for psychologically distressed IT workers, we developed a counseling agent (CA) called a context respectful counseling agent (CRECA), which serves IT workers just like a human counsellor. In a context respectful/ preserving way to provide unconditional positive regard, CRECA replies prompting to dig or clarify problems as well as paraphrases or processes mirroring. In this paper, to save more persons including even elderly people other than IT workers, CRECA is enhanced to realize Virtual Counseling Agent (VCA) as follows: 1) making more human-friendly by an image avatar with voice conversation, 2) letting confirmation replies such as the relationship among wishes, obstacles, etc. as well as with past sayings in client’s utterances, especially for the forgetful/ elderly persons. For successful voice conversation, Google cloud speech API is not only exploited but its error processing is elaborated in our VCA system. The evaluation by 14 subjects showed the effect of this new VCA as follows: 1) the dialogue continuation length became twice as long as that of ELIZA, 2) positive feeling by selfawareness became high score 5 or 6 in 7 stages of Likert scale for all the elderly 7 persons.

Formal methods are a usual means to avoid errors or bugs in the development, adjustment and maintenance of both software and knowledge bases. This chapter provides a formal method to refine a knowledge base based on insides about its correctness derived from its use in practice. The objective of this refinement technique is to overcome particular invalidities revealed by the application of a case-oriented validation technology, i.e. it is some kind of "learning by examples". Approaches from AI or Data Mining to solve such problems are often not useful for a system refinement that aims at is an appropriate modeling of the domain knowledge in way humans would express that, too. Moreover, they often lead to a knowledge base which is difficult to to interpret, because it is too far from a natural way to express domain knowledge. The refinement process presented here is characterized by (1) using human expertise that also is a product of the validation technique and (2) keeping as much as possible of the original humanmade knowledge base. At least the second principle is pretty much adopted from Software Engineering. This chapter provides a brief introduction to AI rule base refinement approaches so far as well as an introduction to a validation and refinement framework for rulebased systems. It also states some basic principles for system refinement, which are adopted from Software Engineering. The next section introduces a refinement approach based on these principles. Moreover, it considers this approach from the perspective of the principles. Finally, some more general conclusions for the development, employment, and refinement of complex systems are drawn. The developed technology covers five steps : (1) test case generation, (2) test case experimentation, (3) evaluation, (4) validity assessment, and (5) system refinement. These steps can be performed iteratively, where the process can be conducted again after the improvements have been made.