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Acoustic Parameter Extraction from Occupied Rooms Utilizing Blind Source Separation

  • Yonggang Zhang
  • Jonathon A. Chambers
  • Paul Kendrick
  • Trevor J. Cox
  • Francis F. Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4253)

Abstract

Room acoustic parameters such as reverberation time (RT) can be extracted from passively received speech signals by some ‘blind’ methods, which mitigates the need for good controlled excitation signals or prior information of the room geometry. However, noise will degrade such methods greatly. In this paper a new framework is proposed to extend these methods for room parameter extraction from noise-free cases to more realistic noise environment, such as occupied rooms, where noises are generated by occupants. In this proposed framework, blind source separation (BSS) is combined with an adaptive noise canceller (ANC) to remove the noise from the passively received reverberant speech signal. Room acoustic parameters can then be extracted from the output of the ANC with existing ‘blind’ methods. As a demonstration we will utilize this framework combined with a maximum-likelihood (ML) based method to estimate the RT of a simulated occupied room. Simulation results show that the proposed framework provides a good estimate of the RT in such a simulated occupied room.

Keywords

Speech Signal Blind Source Separation Reverberation Time Adaptive Noise Canceller Blind Source Separation Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yonggang Zhang
    • 1
  • Jonathon A. Chambers
    • 1
  • Paul Kendrick
    • 2
  • Trevor J. Cox
    • 2
  • Francis F. Li
    • 3
  1. 1.The Centre of Digital Signal Processing, Cardiff School of EngineeringCardiff UniversityCardiffUK
  2. 2.School of Acoustics and Electronic EngineeringUniversity of SalfordSalfordUK
  3. 3.Department of Computing and MathematicsManchester Metropolitan UniversityManchesterUK

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