An active audition framework for auditory-driven HRI: Application to interactive robot dancing

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2012

Autores

oliveira, jl (Autor) Outra; ince, g (Autor) Outra; nakamura, k (Autor) Outra; nakadai, k (Autor) Outra; okuno, hg (Autor) Outra; reis, lp (Autor) FEUP; gouyon, f (Autor) FEUP

Ata de Conferência Internacional

Título: Proceedings - IEEE International Workshop on Robot and Human Interactive Communication

Páginas: 1078-1085

2012 21st IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2012

Paris, 9 September 2012 through 13 September 2012

Indexação

ISI Web of Knowledge

Scopus - 10 Citações

Outras Informações

ID Authenticus: P-008-7WW

DOI: 10.1109/roman.2012.6343892

Abstract (EN): 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 non-verbal 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. © 2012 IEEE.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8