Chatbot

About: Chatbot is a research topic. Over the lifetime, 2415 publications have been published within this topic receiving 24372 citations. The topic is also known as: IM bot & AI chatbot.

Usefulness, localizability, humanness, and language-benefit: additional evaluation criteria for natural language dialogue systems

Abstract: Human---computer dialogue systems interact with human users using natural language. We used the ALICE/AIML chatbot architecture as a platform to develop a range of chatbots covering different languages, genres, text-types, and user-groups, to illustrate qualitative aspects of natural language dialogue system evaluation. We present some of the different evaluation techniques used in natural language dialogue systems, including black box and glass box, comparative, quantitative, and qualitative evaluation. Four aspects of NLP dialogue system evaluation are often overlooked: "usefulness" in terms of a user's qualitative needs, "localizability" to new genres and languages, "humanness" or "naturalness" compared to human---human dialogues, and "language benefit" compared to alternative interfaces. We illustrated these aspects with respect to our work on machine-learnt chatbot dialogue systems; we believe these aspects are worthwhile in impressing potential new users and customers.

A Large-Scale User Study of an Alexa Prize Chatbot: Effect of TTS Dynamism on Perceived Quality of Social Dialog

Abstract: This study tests the effect of cognitive-emotional expression in an Alexa text-to-speech (TTS) voice on users’ experience with a social dialog system. We systematically introduced emotionally expressive interjections (e.g., “Wow!”) and filler words (e.g., “um”, “mhmm”) in an Amazon Alexa Prize socialbot, Gunrock. We tested whether these TTS manipulations improved users’ ratings of their conversation across thousands of real user interactions (n=5,527). Results showed that interjections and fillers each improved users’ holistic ratings, an improvement that further increased if the system used both manipulations. A separate perception experiment corroborated the findings from the user study, with improved social ratings for conversations including interjections; however, no positive effect was observed for fillers, suggesting that the role of the rater in the conversation—as active participant or external listener—is an important factor in assessing social dialogs.

The Impact of Chatbots on Customer Loyalty: A Systematic Literature Review

Abstract: More and more companies have implemented chatbots on their websites to provide support to their visitors on a 24/7 basis. The new customer wants to spend less and less time and therefore expects to reach a company anytime and anywhere, regardless of time, location, and channel. This study provides insight into the influence of chatbots on customer loyalty. System quality, service quality, and information quality are crucial dimensions that a chatbot must meet to give a good customer experience. To make a chatbot more personal, companies can alter the language style. Human-like chatbots lead to greater satisfaction and trust among customers, leading to greater adoption of the chatbot. The results of this study showed that a connection between chatbots and customer loyalty is very likely. Besides, some customers suffer from the privacy paradox because of personalization. Implications of this study are discussed.

Nombot: simplify food tracking

Abstract: Quantified self is a growing research area in human -- computer interaction. New techniques help users to track and optimize their daily activities. Some data is collected automatically. Others like information about nutrition have to be entered manually by the user. This process is labor -- intensive and quite often the motivation is fading over the time. In this paper, an approach is introduced to simplify food tracking. This developed procedure assimilates into daily routines. The instant messaging service called Telegram is used to propose the chatbot Nombot to the user. This bot communicates with the user and collects data about the nutrition of its chat partner. Different motivation types are considered. To evaluate the described implementation, an A/B study is conducted.

Nabiha: An Arabic Dialect Chatbot

Abstract: Nowadays, we are living in the era of technology and innovation that impact various fields, including sciences. In computing and technology, many outstanding and attractive programs and applications have emerged, including programs that try to mimic the human behavior. A chatbot is an example of the artificial intelligence-based computer programs that try to simulate the human behavior by conducting a conversation and an interaction with the users using natural language. Over the years, various chatbots have been developed for many languages (such as English, Spanish, and French) to serve many fields (such as entertainment, medicine, education, and commerce). Unfortunately, Arabic chatbots are rare. To our knowledge, there is no previous work on developing a chatbot for the Saudi Arabic dialect. In this study, we have developed “Nabiha,” a chatbot that can support conversation with Information Technology (IT) students at King Saud University using the Saudi Arabic dialect. Therefore, Nabiha will be the first Saudi chatbot that uses the Saudi dialect. To facilitate access to Nabiha, we have made it available on different platforms: Android, Twitter, and Web. When a student wants to talk with Nabiha, she can download an application, talk with her on Twitter, or visit her website. Nabiha was tested by the students of the IT department, and the results were somewhat satisfactory, considering the difficulty of the Arabic language in general and the Saudi dialect in particular.