IBN@speech: Cognitive Framework for Intent Translation

The IBN@speech framework introduces a novel approach to network management by integrating an Intent Translation Engine with speech recognition technology. This system allows users to issue natural language voice commands, which are translated into network configurations and implemented via the Open Network Operating System (ONOS). Unlike traditional methods that rely on fixed databases, IBN @ speech leverages a combination of rule based systems and RASA based conversational AI to offer a user friendly interface, significantly enhancing network automation through real time adjustments and efficient service deployment. Our initial results demonstrate notable improvements in service deployment time and user satisfaction, positioning IBN @ speech as a compelling alternative to conventional network management techniques.

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Published
2025-01-10
DOI
https://doi.org/10.1109/ccnc54725.2025.10976062
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

IBN@speech: Cognitive Framework for Intent Translation

Wang‐Cheol Song, Muhammad Asif, Talha Ahmed Khan
Natural Language Processing Techniques
article

IBN@speech: Cognitive Framework for Intent Translation

Wang‐Cheol Song, Muhammad Asif, Talha Ahmed Khan
article en

Abstract

The IBN@speech framework introduces a novel approach to network management by integrating an Intent Translation Engine with speech recognition technology. This system allows users to issue natural language voice commands, which are translated into network configurations and implemented via the Open Network Operating System (ONOS). Unlike traditional methods that rely on fixed databases, IBN @ speech leverages a combination of rule based systems and RASA based conversational AI to offer a user friendly interface, significantly enhancing network automation through real time adjustments and efficient service deployment. Our initial results demonstrate notable improvements in service deployment time and user satisfaction, positioning IBN @ speech as a compelling alternative to conventional network management techniques.

University of Surrey (GB), Jeju National University (KR)
National Research Foundation of Korea
Openalex Percentile: Top 96%
Natural Language Processing Techniques
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IBN@speech: Cognitive Framework for Intent Translation — Wang‐Cheol Song, Muhammad Asif, et al. · (2025) | TGRS Research Map | TGRS