A Dissonant Frequency Filtering for Enhanced Clarity of Husky Voice Signals

  • Sangki Kang
  • Yongserk Kim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4188)


In general, added noise in clean signal reduces intelligibility and degrades the performance of speech processing algorithms used for the applications such as speech compression and recognition. In this paper, a new voice clarity enhancing method using a dissonant frequency filtering (DFF) (especially C # and F # in each octave band when reference frequency is C) combined with noise suppression (NS) is proposed. The proposed method targets for speakers whose intelligibility became worse than normal under both noisy and noiseless environments.

The test results indicate that the proposed method provides a significant audible improvement for speakers whose intelligibility is impaired and especially for the speech contaminated by the colored noise. Therefore when the filter is employed as a pre-filter for enhancing the clarity of husky voice where several types of noises are also exploited, the output speech quality and clarity can be greatly enhanced.


Colored Noise Noise Suppression Speech Enhancement Octave Band Adaptive Noise 
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

  • Sangki Kang
    • 1
  • Yongserk Kim
    • 1
  1. 1.SW Lab., Telecommunication R&D Center, Telecommunication Network Business, Samsung Electronics Co.Korea

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