We present HERO, a Conversational Intelligent Assistant to support workers in industrial domains. The proposed system is able to interact with humans using natural language and observing the surrounding world in order to avoid the language ambiguity. HERO is composed of four modules: 1) the input module to process both text and visual signals, 2) the NLP module to predict user intent and extract relevant entities from text, 3) the object detection module to extract entities by analyzing images captured by the user and 4) the output module which is responsible for choosing the best answer to send to the user. To assess its usefulness in a real scenario, the proposed system is implemented and evaluated in an industrial laboratory setting. Preliminary experiments show that HERO achieves good performance in predicting intents and entities exploiting both text and visual signals.

HERO: An Artificial Conversational Assistant to Support Humans in Industrial Scenarios

Ragusa, F;Leonardi, R;Furnari, A;Farinella, GM
2022-01-01

Abstract

We present HERO, a Conversational Intelligent Assistant to support workers in industrial domains. The proposed system is able to interact with humans using natural language and observing the surrounding world in order to avoid the language ambiguity. HERO is composed of four modules: 1) the input module to process both text and visual signals, 2) the NLP module to predict user intent and extract relevant entities from text, 3) the object detection module to extract entities by analyzing images captured by the user and 4) the output module which is responsible for choosing the best answer to send to the user. To assess its usefulness in a real scenario, the proposed system is implemented and evaluated in an industrial laboratory setting. Preliminary experiments show that HERO achieves good performance in predicting intents and entities exploiting both text and visual signals.
2022
978-989-758-591-3
First Person Vision
Object Detection
Chatbot
Conversational Agent
Visual Question Answering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/540578
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