As we evaluate each sentence, we can program our chatbot to also take into consideration the emotional level of the user input. Normally the analyzer vectorices the sentence, returning a float value, depending on the model the index value can then be used to trigger a response.īased on the index range we can extract the emotional level of each response. As each user sentence is captured during a chat session, it can be evaluated for negative sentiment. With sentiment analysis tools we can try to detect the emotional level of an individual on the per sentences bases. If we are able to detect and analyze each user response to obtain an emotional index, we could use this information then to help us monitor the level of satisfaction of a customer. The only way we are able to capture emotions in a chatbot is through sentiment analysis of a chat, posing its own set of challenges. Detecting an emotional response requires multisensorial awareness, something most of us do instinctively. ![]() ![]() Chat Robot technology is still early and much of the focus has been on the basic question/answer interaction.Īlthough some chatbots have been trained to be incredibly accurate in their response, most lack the ability to monitor the human emotion and perhaps for good reason.Įmotions vary not only among individuals but also within a person and the moment. As chatbots become more popular in the marketplace assisting companies to manage customer interaction, it is important to provide a high-level customer experience.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |