Alle Publikationen

  • Erweiterte Suche öffnen

Treffer: 2
  • <<
  • 1
  • 2017

  • Bastianelli, Emanuele (2017): Structured learning for spoken language understanding in human-robot interaction. In: INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 36 (5-7), S. 660-683

    Abstract: Robots are slowly becoming a part of everyday life, being marketed for commercial applications such as telepresence, cleaning or entertainment. Thus, the ability to interact via natural language with non-expert users is becoming a key requirement. Even if user utterances can be efficiently recognized and transcribed by automatic speech recognition systems, several issues arise in translating them into suitable robotic actions and most of the existing solutions are strictly related to a specific scenario. In this paper, we present an approach to the design of natural language interfaces for human robot interaction, to translate spoken commands into computational structures that enable the robot to execute the intended request. The proposed solution is achieved by combining a general theory of language semantics, i.e. frame semantics, with state-of-the-art methods for robust spoken language understanding, based on structured learning algorithms. The adopted data driven paradigm allows the development of a fully functional natural language processing chain, that can be initialized by re-using available linguistic tools and resources. In addition, it can be also specialized by providing small sets of examples representative of a target newer domain. A systematic benchmarking resource, in terms of a rich and multi-layered spoken corpus has also been created and it has been used to evaluate the natural language processing chain. Our results show that our processing chain, trained with generic resources, provides a solid baseline for command understanding in a service robot domain. Moreover, when domain-dependent resources are provided to the system, the accuracy of the achieved interpretation always improves.

  • 1997

  • Gigerenzer, Gerd (1997) : The modularity of social intelligence In: Whiten, Andrew; Byrne, Richard W. (Hg.): Machiavellian intelligence II. Extensions and evaluations: Cambridge: Cambridge University Press, S. 264-288

    Abstract: Argues that the social intelligence hypothesis, while stimulating and exciting, is vague and imprecise, and that some of its propositions are empirically empty and should be dropped. A "modular" version of the social intelligence hypothesis is proposed, which offers a specific theory about the mechanisms of social intelligence. Assumptions of this hypothesis are discussed in detail and an example of an experimental test of the resulting predictions illustrates that the hypothesis produces testable predictions and can explain apparently contradictory data previously considered irrational. It is argued that the investigation of social intelligence should be driven by theory and empirically tested and that the modular version outlined offers a starting point.

  • <<
  • 1