OREANDA-NEWS. Fujitsu Laboratories Ltd. today announced the development of technology that can be easily set up and autonomously carry on a dialogue, based on AI technology, while accurately understanding a user's request and naturally eliciting the necessary information. The technology is intended primarily for customer service support.

With previous technology, dialogue with computers required preparations of dialogue scenarios laying out how to respond when certain things are said, and business systems usually operated based on these scenarios. Now Fujitsu Laboratories has developed a new technology that can structurally extract the relationships between word meanings of input text to deal with the multiple meanings, ambiguity and other problems particular to Japanese language expressions, enabling a highly accurate understanding of users' speech and realizing smooth dialogue. In addition, by properly incorporating information from external databases, such as linked open data (LOD)(1), while also using a knowledge-based dialogue creation technology that automatically learns response options for natural dialogue from records, Fujitsu Laboratories has developed technology that can autonomously conduct dialogue.

Through these technologies, information service providers can quickly implement a system that suggests recommended products and service plans through a natural dialogue user interface, without preparing complicated scenarios based on their services ahead of time.

Moreover, Fujitsu Laboratories carried out a field trial of these technologies on certain customer support tasks for Tokio Marine & Nichido Fire Insurance Co., Ltd. The field trial demonstrated that correct responses could be achieved during a natural conversation.

These technologies use Fujitsu Limited's AI technology, Human Centric AI Zinrai.

These technologies will be exhibited at Fujitsu Forum 2016, which will be held at the Tokyo International Forum on May 19-20.

Currently, messaging applications for users to conduct dialogue with a system are becoming familiar as a method of communication on smartphones. In addition, in order to apply this, there have been a number of public APIs for these message applications to let users converse with systems, and there are increasing expectations that dialogue systems will be implemented for a variety of services. At the same time, in order to use this sort of dialogue system for business applications with a clear goal, unless the system designer is an expert with a certain level of knowledge, it was impossible to create dialogue scenarios that could easily obtain the necessary information from the user.

With previous technology, in order to have a dialogue with a computer, it was necessary to prepare dialogue scenarios laying out how to respond when certain things are said, and business systems usually operated based on these scenarios. For these types of scenarios, it was necessary to record expected user statements in advance. This meant that, because it was necessary to also think of scenarios to return the dialogue to its goal if the user made an off-topic statement, and because it was necessary to prepare these scenarios for each task or service, the time required to build and implement dialogue systems was an issue.