Spoken Language Understanding in Interactive Robotics provides computational models of human-machine communication based on the vocal input. However, robots operate in specific environments and the correct interpretation of the spoken sentences depends on the physical, cognitive and linguistic aspects triggered by the operational environment. Grounded language processing should exploit both the physical constraints of the context as well as knowledge assumptions of the robot. These include the subjective perception of the environment that explicitly affects linguistic reasoning. In this work, a standard linguistic pipeline for semantic parsing is extended toward a form of perceptually informed natural language processing that combines discriminative learning and distributional semantics. Empirical results achieve up to a 40% of relative error reduction.

Bastianelli, E., Croce, D., Vanzo, A., Basili, R., Nardi, D. (2016). A discriminative approach to grounded spoken language understanding in interactive robotics. In IJCAI International Joint Conference on Artificial Intelligence (pp.2747-2753). International Joint Conferences on Artificial Intelligence.

A discriminative approach to grounded spoken language understanding in interactive robotics

BASTIANELLI, EMANUELE;CROCE, DANILO;BASILI, ROBERTO;
2016-01-01

Abstract

Spoken Language Understanding in Interactive Robotics provides computational models of human-machine communication based on the vocal input. However, robots operate in specific environments and the correct interpretation of the spoken sentences depends on the physical, cognitive and linguistic aspects triggered by the operational environment. Grounded language processing should exploit both the physical constraints of the context as well as knowledge assumptions of the robot. These include the subjective perception of the environment that explicitly affects linguistic reasoning. In this work, a standard linguistic pipeline for semantic parsing is extended toward a form of perceptually informed natural language processing that combines discriminative learning and distributional semantics. Empirical results achieve up to a 40% of relative error reduction.
25th International Joint Conference on Artificial Intelligence, IJCAI 2016
usa
2016
AI Journal
Rilevanza internazionale
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
Settore INF/01 - Informatica
English
Artificial Intelligence
http://www.ijcai.org/
Intervento a convegno
Bastianelli, E., Croce, D., Vanzo, A., Basili, R., Nardi, D. (2016). A discriminative approach to grounded spoken language understanding in interactive robotics. In IJCAI International Joint Conference on Artificial Intelligence (pp.2747-2753). International Joint Conferences on Artificial Intelligence.
Bastianelli, E; Croce, D; Vanzo, A; Basili, R; Nardi, D
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2108/189348
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