Paper Title
Intelligent Assistance Survey
Abstract
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.