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September 2012

An Active Audition Framework for Auditory-driven HRI: Application to Interactive Robot Dancing

  • J. L. Oliveira, G. Ince, K. Nakamura, K. Nakadai, H. G. Okuno, L. P. Reis, F. Gouyon,
  • in Proceedings of the 21st IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2015),
  • IEEE,
  • 2012,
  • pp. 1078-1085,
  • Conference paper

In this paper we propose a general active audition framework for auditory-driven Human-Robot Interaction (HRI). The proposed framework simultaneously processes speech and music on-the-fly, integrates perceptual models for robot audition, and supports verbal and non-verbal interactive communication by means of (pro)active behaviors. To ensure a reliable interaction, on top of the framework a behavior decision mechanism based on active audition policies the robot’s actions according to the reliability of the acoustic signals for auditory processing. To validate the framework’s application to general auditory-driven HRI, we propose the implementation of an interactive robot dancing system. This system integrates three preprocessing robot audition modules: sound source localization, sound source separation, and ego noise suppression; two modules for auditory perception: live audio beat tracking and automatic speech recognition; and multi-modal behaviors for verbal and nonverbal interaction: music-driven dancing and speech-driven dialoguing. To fully assess the system, we set up experimental and interactive real-world scenarios with highly dynamic acoustic conditions, and defined a set of evaluation criteria. The experimental tests revealed accurate and robust beat tracking and speech recognition, and convincing dance beat-synchrony. The interactive sessions confirmed the fundamental role of the behavior decision mechanism for actively maintaining a robust and natural human-robot interaction.

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