A “small-data”-driven approach to dialogue systems for natural language human computer interaction

Author(s):  
Tiberiu Boros ◽  
Stefan Daniel Dumitrescu
2021 ◽  
Vol 11 (13) ◽  
pp. 6057
Author(s):  
Ching-Han Chen ◽  
Ming-Fang Shiu ◽  
Shu-Hui Chen

Dialogue in natural language is the most important communication method for the visually impaired. Therefore, the dialogue system is the main subsystem in the visually impaired navigation system. The purpose of the dialogue system is to understand the user’s intention, gradually establish context through multiple conversations, and finally provide an accurate destination for the navigation system. We use the knowledge graph as the basis of reasoning in the dialogue system, and then update the knowledge graph so that the system gradually conforms to the user’s background. Based on the experience of using the knowledge graph in the navigation system of the visually impaired, we expect that the same framework can be applied to more fields in order to improve the practicality of natural language dialogue in human–computer interaction.


1996 ◽  
Vol 28 (3) ◽  
pp. 102-107 ◽  
Author(s):  
Oliviero Stock ◽  
Carlo Strapparava ◽  
Massimo Zancanaro

Author(s):  
Tanveer J. Siddiqui ◽  
Uma Shanker Tiwary

Spoken dialogue systems are a step forward towards the realization of human-like interaction with computer-based systems. This chapter focuses on issues related to spoken dialog systems. It presents a general architecture for spoken dialogue systems for human-computer interaction, describes its components, and highlights key research challenges in them. One important variation in the architecture is modeling knowledge as a separate component. This is unlike existing dialogue systems in which knowledge is usually embedded within other components. This separation makes the architecture more general. The chapter also discusses some of the existing evaluation methods for spoken dialogue systems.


2021 ◽  
Author(s):  
Anish Acharya ◽  
Suranjit Adhikari ◽  
Sanchit Agarwal ◽  
Vincent Auvray ◽  
Nehal Belgamwar ◽  
...  

2021 ◽  
Author(s):  
Russell J Jarvis ◽  
Patrick M. McGurrin ◽  
Rebecca Featherston ◽  
Marc Skov Madsen ◽  
Shivam Bansal ◽  
...  

Here we present a new text analysis tool that consists of a text analysis service and an author search service. These services were created by using or extending many existing Free and Open Source tools, including streamlit, requests, WordCloud, TextStat, and The Natural Language Tool Kit. The tool has the capability to retrieve journal hosting links and journal article content from APIs and journal hosting websites. Together, these services allow the user to review the complexity of a scientist’s published work relative to other online-based text repositories. Rather than providing feedback as to the complexity of a single text as previous tools have done, the tool presented here shows the relative complexity across many texts from the same author, while also comparing the readability of the author’s body of work to a variety of other scientific and lay text types. The goal of this work is to apply a more data-driven approach that provides established academic authors with statistical insights into their body of published peer reviewed work. By monitoring these readability metrics, scientists may be able to cater their writing to reach broader audiences, contributing to an improved global communication and understanding of complex topics.


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