Sensor Systems and Software. 7th International Conference, S-Cube 2016, Sophia Antipolis, Nice, France, December 1-2, 2016, Revised Selected Papers

Research Article

iHouse: A Voice-Controlled, Centralized, Retrospective Smart Home

Download
229 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-61563-9_6,
        author={Benjamin V\o{}lker and Tobias Schubert and Bernd Becker},
        title={iHouse: A Voice-Controlled, Centralized, Retrospective Smart Home},
        proceedings={Sensor Systems and Software. 7th International Conference, S-Cube 2016, Sophia Antipolis, Nice, France, December 1-2, 2016, Revised Selected Papers},
        proceedings_a={S-CUBE},
        year={2017},
        month={7},
        keywords={Smart home Retrospective home Offline speech recognition Wake-up-word recognition Distributed speech processing},
        doi={10.1007/978-3-319-61563-9_6}
    }
    
  • Benjamin Völker
    Tobias Schubert
    Bernd Becker
    Year: 2017
    iHouse: A Voice-Controlled, Centralized, Retrospective Smart Home
    S-CUBE
    Springer
    DOI: 10.1007/978-3-319-61563-9_6
Benjamin Völker1,*, Tobias Schubert1,*, Bernd Becker1,*
  • 1: Institute of Computer Science, Albert-Ludwigs-University Freiburg
*Contact email: voelkerb@informatik.uni-freiburg.de, schubert@informatik.uni-freiburg.de, becker@informatik.uni-freiburg.de

Abstract

Speech recognition in smart home systems has become popular in both, research and consumer areas. This paper introduces an innovative concept for a modular, customizable, and voice-controlled smart home system. The system combines the advantages of distributed and centralized processing to enable a secure as well as highly modular platform and allows to add existing non-smart components retrospectively into the smart environment. To interact with the system in the most comfortable way - and in particular without additional devices like smartphones - voice-controlling was added as the means of choice. The task of speech recognition is partitioned into decentral Wake-Up-Word (WUW) recognition and central continuous speech recognition to enable flexibility while maintaining security. This is achieved utilizing a novel WUW algorithm suitable to be executed on small microcontrollers which uses Mel Frequency Cepstral Coefficients as well as Dynamic Time Warping. A high rejection rate up to 99.93% was achieved, justifying the use of the algorithm as a voice trigger in the developed smart home system.