Mixed sound event verification on wireless sensor network for home automation

Jia Ching Wang, Chang Hong Lin, Ernestasia Siahaan, Bo Wei Chen, Hsiang Lung Chuang

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


In this paper, we present the problem of mixed sound event verification in a wireless sensor network for home automation systems. In home automation systems, the sound recognized by the system becomes the basis for performing certain tasks. However, if a target source is mixed with another sound due to simultaneous occurrence, the system would generate poor recognition results, subsequently leading to inappropriate responses. To handle such problems, this study proposes a framework, which consists of sound separation and sound verification techniques based on a wireless sensor network (WSN), to realize sound-triggered automation. In the sound separation phase, we present a convolutive blind source separation system with source number estimation using time-frequency clustering. An accurate mixing matrix can be estimated by the proposed phase compensation technique and used for reconstructing the separated sound sources. In the verification phase, Mel frequency cepstral coefficients and Fisher scores that are derived from the wavelet packet decomposition of signals are used as features for support vector machines. Finally, a sound of interest can be selected for triggering automated services according to the verification result. The experimental results demonstrate the robustness and feasibility of the proposed system for mixed sound verification in WSN-based home environments.

Original languageEnglish
Article number6514931
Pages (from-to)803-812
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Issue number1
StatePublished - Feb 2014


  • Blind source separation (BSS)
  • home automation
  • sound verification
  • support vector machine (SVM)
  • wireless sensor network (WSN)


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