Natural Language Generation in Artificial Intelligence and Computational Linguistics

1991 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Natural Language ◽  
Computational Linguistics ◽  
Natural Language Generation ◽  
Language Generation

ProBot – A Procedure Chatbot for Digital Procedural Adherence

2020 ◽  
Vol 64 (1) ◽  
pp. 224-228
Author(s):  
Nilesh Ade ◽  
Noor Quddus ◽  
Trent Parker ◽  
S.Camille Peres
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Natural Language ◽  
Industry 4.0 ◽  
Natural Language Generation ◽  
Conversational Agent ◽  
Safe Distance ◽  
Process Industries ◽  
Language Generation ◽  
Plastic Pellets

One of the major implications of Industry 4.0 will be the application of digital procedures in process industries. Digital procedures are procedures that are accessed through a smart gadget such as a tablet or a phone. However, like paper-based procedures their usability is limited by their access. The issue of accessibility is magnified in tasks such as loading a hopper car with plastic pellets wherein the operators typically place the procedure at a safe distance from the worksite. This drawback can be tackled in the case of digital procedures using artificial intelligence-based voice enabled conversational agent (chatbot). As a part of this study, we have developed a chatbot for assisting digital procedure adherence. The chatbot is trained using the possible set of queries from the operator and text from the digital procedures through deep learning and provides responses using natural language generation. The testing of the chatbot is performed using a simulated conversation with an operator performing the task of loading a hopper car.

Lying and Computational Linguistics

2018 ◽  
pp. 419-435
Author(s):  
Kees van Deemter ◽  
Ehud Reiter
Keyword(s):  
Theoretical Model ◽  
Natural Language ◽  
Computational Linguistics ◽  
Simple Game ◽  
Natural Language Generation ◽  
Language Generation ◽  
Game Theoretical Model

This chapter espouses an engineering perspective on lying, showing how various departures from the truth arise naturally when computers talk about data. We start by explaining how Natural Language Generation (NLG) systems work when they talk about data. Then we discuss how, perhaps surprisingly, such systems cannot help deviating from the truth in two different ways, namely, by omitting information, and by generating statements whose truth is questionable; we illustrate our account with examples from practical NLG systems. Next, we discuss briefly why NLG systems should arguably deviate from the truth in other, more deliberate ways as well, after which we sketch a simple game-theoretical model that can help to explain our observations. We conclude by summing up what the engineering view tells us about lying, whether it is people or computers that take the floor.

Integration of Artificial Intelligence Into Austrian Journalism

2021 ◽  
pp. 182-200
Author(s):  
Cigdem Elikci
Keyword(s):  
Artificial Intelligence ◽  
Natural Language ◽  
Natural Language Generation ◽  
Status Quo ◽  
Potential Threat ◽  
Language Generation ◽  
News Consumption ◽  
The Status ◽  
Filter Bubbles

This chapter aims to highlight the changes that journalism in Austria should expect. The authors analyse the data collected on Austrians' habits of consuming news through intelligent virtual assistants (IVAs). Furthermore, the importance and potential of the devices run by artificial intelligence (AI), such as IVAs and natural language generation software, are highlighted. The status quo and Austrian journalists' knowledge about IVAs and their predictions about the attitude of citizens towards those devices are outlined. AI in journalism industry is not only discussed as an assistant to ease the workflow of journalists in Austria; it is also represented as a potential threat which creates filter bubbles due to personalized news consumption through IVAs.

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