Survey on Chatbot Design Techniques in Speech Conversation Systems

By Sameera A'amer Abdul-Kader, John Woods. 2015

459 citations recorded by the source corpus.

Human-Computer Speech is gaining momentum as a technique of computer interaction. There has been a recent upsurge in speech based search engines and assistants such as Siri, Google Chrome and Cortana. Natural Language Processing (NLP) techniques such as NLTK for Python can be applied to analyse speech, and intelligent responses can be found by designing an engine to provide appropriate human like responses. This type of programme is called a Chatbot, which is the focus of this study. This paper presents a survey on the techniques used to design Chatbots and a comparison is made between different design techniques from nine carefully selected papers according to the main methods adopted. These papers are representative of the significant improvements in Chatbots in the last decade. The paper discusses the similarities and differences in the techniques and examines in particular the Loebner prize-winning Chatbots.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/cb4a4f326c925009c6f575d1874dea056c731b63

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In Artificial Intelligence

Citations in the corpus

A Literature Survey of Recent Advances in Chatbots (2021, methodology): “[30] compare design techniques drawn from nine selected papers.”
How Should My Chatbot Interact? A Survey on Social Characteristics in Human–Chatbot Interaction Design (2019, methodology): “aningful answers: some chatbots use simplistic approaches, like pattern matching rules based on keywords or template phrases applied in the last user utterance, to find the most appropriate response [Abdul-Kader and Woods 2015; Ramesh et al. 2017]. However, as the chatbot does not interpret the mean”
Text Style Transfer: A Review and Experiment Evaluation (2020, background): “The research and development of chatbots, i.e., intelligent dialogue systems that are able to engage in conversations with humans, has been one of the longest-running goals in artificial intelligence [1, 80, 95].”
MamaBot: a System based on ML and NLP for supporting Women and Families during Pregnancy (2018, unknown): “in [17] presented the design techniques”
"Hey Alexa, What's Up?": A Mixed-Methods Studies of In-Home Conversational Agent Usage (2018, background): “Therefore, they must be designed with particular strategies in mind [1,15].”