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Distant Speech Recognition in Smart Homes Initiated by Hand Clapping within Noisy Environments . Florian Bacher & Christophe Sourisse. [623.400] Seminar in Interactive Systems. Agenda. Introduction Methodology Experiment Description Implementation Results Conclusion. Introduction.
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Distant Speech Recognition in Smart Homes Initiated by Hand Clapping within Noisy Environments. Florian Bacher & Christophe Sourisse [623.400] Seminar in Interactive Systems
Agenda • Introduction • Methodology • Experiment Description • Implementation • Results • Conclusion
Introduction • Smart homes have become a major field of research in information and communication technologies. • Possible way of interaction: Voice commands. • Goal of our experiment:evaluate the possibility of recognizing voice commands initiated by hand claps in a noisy environment. • Gather a set of voice commands uttered by various speakers.
Methodology • Main method: Lecouteux et al. [1] • Deals with speech recognition within distress situations. • Problem: no background noise was considered. • Chosen methodology: adapt Lecouteux et al. protocol considering: • Noisy settings. • Initiating recognition using hand claps.
Methodological issues • Choice of the room setting • Lecouteux et al. [1]: a whole flat. • Vovos et al. []: one-room microphone array. • Choice: one room with 2 microphones. • Choice of background noises
Experiment Settings • Performed in a 3m x 3m room. • Sounds were captured by two microphones which were hidden in the room.
Experiment Description • 20 participants (10 men, 10 women, 25,5 ± 11 years) participated to a 2-phase exp. • 1st phase: recognize a word (“Jeeves”) as a command • System’s attention is catched by double clapping. • 4 scenarios. • Background noises tested: step noises, opening doors, moving chairs, radio show. • 2nd phase: Gather a set of voicecommands • List of 15 command-words. • Reference record for pronounciation issues. • Eachwordisuttered 10 times.
Implementation • Used technologies: • C# Library System.Speech.Recognition: Interface to the Speech Recognition used by Windows. • Microphones: Two dynamic microphones with cardioid polar pattern (Sennheiser BF812/e8155) • Line6 UX1 Audio Interface • Line6 Pod Farm 2.5
Implementation • Signal is captured in real time. • If there are exactly two signal peaks within a certain timeframe, the software classifies them as a double clap. • After a double clap has been detected, the actual speech recognition engine is activated (i.e. the software is waiting for commands).
Conclusion • A new idea of how to initiate speech recognition in human computer interaction. • An evaluation of the potential influence of a noisy environment. • Results: encouraging, but not yet satisfying. • Next step: perform this experiment in a real smart-home-context.
References • [1] B. Lecouteux, M. Vacher and F. Portet. Distant speech recognition in a smart home: comparison of several multisouce ASRs in realistic conditions. Interspeech., 2011. • [2] A. Fleury, N. Noury, M. Vacher, H. Glasson and J.-F. Serignat. Sound and speech detection and classification in a health smart home. 30th Annual International IEEE EMBS Conference, Vancouver, British Columbia, Canada, August 2008. • [3] M. Vacher, N. Guirand, J.-F. Serignat and A. Fleury. Speech recognition in a smart home: Some experiments for telemonitoring. Proceedings of the 5th Conference on Speech Technology and Human-Computer Dialogue, pages 1 – 10, June 2009. • [4] J. Rouillard and J.-C. Tarby. How to communicate smartly with your house? Int. J. Ad Hoc and Ubiquitous Computing, 7(3), 2011. • [5] S. Moncrief, S. Venkatesh, G. West, and S. Greenhill. Incorporating contextual audio for an actively anxious smart home. Proceedings of the 2005 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, pages 373 – 378, Dec. 2005. • [6] M. Vacher, D. Istrate, F. Portet, T. Joubert, T. Chevalier, S. Smidtas, B. Meillon, B. Lecouteux, M. Sehili, P. Chahuara and S. Méniard. The sweet-home project: Audio technology in smart homes to improve well-being and reliance. 33rd Annual International IEEE EMBS Conference, Boston, Massachusetts, USA, 2011.
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