Speech "siglet" detection for business microscope

Jun Nishimura, Nobuo Sato, Tadahiro Kuroda

研究成果: Conference contribution

14 被引用数 (Scopus)

抄録

"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.

本文言語English
ホスト出版物のタイトル6th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2008
ページ147-152
ページ数6
DOI
出版ステータスPublished - 2008
外部発表はい
イベント6th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2008 - Hong Kong, Hong Kong
継続期間: 2008 3月 172008 3月 21

出版物シリーズ

名前6th Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2008

Other

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

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 通信

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