Speech "siglet" detection for business microscope

Jun Nishimura, Nobuo Sato, Tadahiro Kuroda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

"Business Microscope" is a tool which provides knowledge workers with a bird-eye view of their daily communication. To meet the problem of the energy consumption of sensor nodes and privacy concerns for wearers and non-wearers, "siglet" sensing is proposed. Siglet sensing is a way to capture very short and noise-like signals by sensors operating on a low duty ratio. To extract the useful information on workers' communication, speech siglet detection is studied. The LBG trained speech and workplace nonspeech models with Mel Frequency Cepstrum Coefficients (MFCCs) as feature vectors are utilized. A hierarchical pruning technique is studied to reduce the calculation cost of the matching process to nearly 25% and refine the classification accuracy. Our approach achieved average speech and nonspeech classification accuracy of 99.96% on 0. 1s long test siglets.

Original languageEnglish
Title of host publication6th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2008
Pages147-152
Number of pages6
DOIs
Publication statusPublished - 2008 Aug 15
Event6th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2008 - Hong Kong, Hong Kong
Duration: 2008 Mar 172008 Mar 21

Publication series

Name6th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2008

Other

Other6th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2008
CountryHong Kong
CityHong Kong
Period08/3/1708/3/21

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Communication

Cite this

Nishimura, J., Sato, N., & Kuroda, T. (2008). Speech "siglet" detection for business microscope. In 6th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2008 (pp. 147-152). [4517388] (6th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2008). https://doi.org/10.1109/PERCOM.2008.83