Introducing the Adaptive Agent Oriented Software Architecture and Its Application in Natural Language User Interfaces

Author(s):  
*Babak Hodjat ◽  
†Makoto Amamiyat
Informatics ◽  
2021 ◽  
Vol 18 (4) ◽  
pp. 40-52
Author(s):  
S. A. Hetsevich ◽  
Dz. A. Dzenisyk ◽  
Yu. S. Hetsevich ◽  
L. I. Kaigorodova ◽  
K. A. Nikalaenka

O b j e c t i v e s. The main goal of the work is a research of the natural language user interfaces and the developmentof a prototype of such an interface. The prototype is a bilingual Russian and Belarusian question-and-answer dialogue system. The research of the natural language interfaces was conducted in terms of the use of natural language for interaction between a user and a computer system. The main problems here are the ambiguity of natural language and the difficulties in the design of natural language interfaces that meet user expectations.M e t ho d s. The main principles of modelling the natural language user interfaces are considered. As an intelligent system, it consists of a database, knowledge machine and a user interface. Speech recognition and speech synthesis components make natural language interfaces more convenient from the point of view of usability.R e s u l t s. The description of the prototype of a natural language interface for a question-and-answer intelligent system is presented. The model of the prototype includes speech-to-text and text-to-speech Belarusian and Russian subsystems, generation of responses in the form of the natural language and formal text.An additional component is natural Belarusian and Russian voice input. Some of the data, required for human voice recognition, are stored as knowledge in the knowledge base or created on the basis of existing knowledge. Another important component is Belarusian and Russian voice output. This component is the top required for making the natural language interface more user-friendly.Co n c l u s i o n. The article presents the research of natural language user interfaces, the result of which provides the development and description of the prototype of the natural language interface for the intelligent question- and-answer system.


1991 ◽  
Vol 1 (4) ◽  
pp. 351-363
Author(s):  
Octavio F. Torres-Chazaro ◽  
Robert J. Beaton ◽  
Michael P. Deisenroth

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2075
Author(s):  
Óscar Apolinario-Arzube ◽  
José Antonio García-Díaz ◽  
José Medina-Moreira ◽  
Harry Luna-Aveiga ◽  
Rafael Valencia-García

Automatic satire identification can help to identify texts in which the intended meaning differs from the literal meaning, improving tasks such as sentiment analysis, fake news detection or natural-language user interfaces. Typically, satire identification is performed by training a supervised classifier for finding linguistic clues that can determine whether a text is satirical or not. For this, the state-of-the-art relies on neural networks fed with word embeddings that are capable of learning interesting characteristics regarding the way humans communicate. However, as far as our knowledge goes, there are no comprehensive studies that evaluate these techniques in Spanish in the satire identification domain. Consequently, in this work we evaluate several deep-learning architectures with Spanish pre-trained word-embeddings and compare the results with strong baselines based on term-counting features. This evaluation is performed with two datasets that contain satirical and non-satirical tweets written in two Spanish variants: European Spanish and Mexican Spanish. Our experimentation revealed that term-counting features achieved similar results to deep-learning approaches based on word-embeddings, both outperforming previous results based on linguistic features. Our results suggest that term-counting features and traditional machine learning models provide competitive results regarding automatic satire identification, slightly outperforming state-of-the-art models.


2014 ◽  
Author(s):  
Sofia Larissa Da Costa ◽  
Valdemar Vicente Graciano Neto ◽  
Juliano Lopes De Oliveira ◽  
Bruno dos Reis Calçado

This paper presents a model-based approach to build Information Systems User Interfaces (ISUI). In this approach, UI presentation and behavioral aspects are modeled as UI Stereotypes, which are high level abstractions of UI appearance and interaction features. A taxonomy of ISUI elements is proposed as the basis for definition of UI stereotypes. These elements are orchestrated on a software architecture which manages model-based UI building and integration with the IS applications. The proposed approach reduces software development efforts and costs, facilitating maintenance and evolution of ISUI. Moreover, UI stereotypes improve usability, consistency, reuse and standardization of both presentation and behavior of ISUI.


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