HUMAN-ROBOT INTERACTION: LANGUAGE ACQUISITION WITH NEURAL NETWORK

Alvin Rindra Fazrie

Abstract


ABSTRACT

The paper gives an overview about the process between two language processing methods towards Human-robot interaction. In this paper, Echo State Networks and Stochastic-learning grammar are explored in order to get an idea about generating human’s natural language and the possibilities of integrating these methods to make the communication process between robot to robot or robot to human to be more natural in dialogic syntactic language game. The methods integration could give several benefits such as improving the communicative efficiency and producing the more natural communication sentence.

 

ABSTRAK

Tulisan ini memberikan penjabaran mengenai dua metode pemrosesan bahasa alami pada interaksi Manusia dan Robot. Echo State Networks adalah salah satu arsitektur dari Jaringan Syaraf Tiruan yang berdasarkan prinsip Supervised Learning untuk Recurrent Neural Network, dieksplorasi bersama Stochastic-learning Grammar yaitu salah satu framework tata bahasa dengan konsep probabilistik yang bertujuan untuk mendapatkan ide bagaimana proses bahasa alami dari manusia dan kemungkinannya mengintegrasikan dua metode tersebut untuk membuat proses komunikasi antara robot dengan robot atau robot dengan manusia menjadi lebih natural dalam dialogic syntactic language game. Metode integrasi dapat memberikan beberapa keuntungan seperti meningkatkan komunikasi yang efisien dan dapat membuat konstruksi kalimat saat komunikasi menjadi lebih natural.

How To Cite : Fazrie, A.R. (2018). HUMAN-ROBOT INTERACTION: LANGUAGE ACQUISITION WITH NEURAL NETWORK. Jurnal Teknik Informatika, 11(1), 75-84.  doi 10.15408/jti.v11i1.6093

Permalink/DOI: http://dx.doi.org/10.15408/jti.v11i1.6093


 


Keywords


Language Acquisition, Language Processing, Human-Robot Interaction, Echo State Network, Stochastic Grammar

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References


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