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Low Complexity Speech Enhancement Algorithm for Improved Perception in Mobile Devices

  • B. S. Premananda
  • B. V. Uma
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 131)

Abstract

In mobile phones, perceived quality of speech signal deteriorates significantly in the presence of background noise since near-end/surrounding noise also arrives at the near-end listener’s ears. The quality of the received signal varies widely depending upon signal strength and unavoidable background noise in the user environment. There is a need to improve the quality of received speech signal in noisy conditions by developing the speech enhancement algorithms. This paper focuses on the impact of the various background noises on signal perception and mechanisms to mitigate the noise impact for improved signal perception. Gain adjustment process with simple time domain approach has been adapted to improve the quality and intelligibility of the speech signal in the noisy environments by automatically increasing output levels when the noise dominates. Since time domain approach has been used, it is less complex and consumes very less battery power of the mobile and also efficiently masks the background noise. This paper studies the effect of various signal parameters on automatic gain adjustment of the received signal to enhance its perception.

Keywords

Adaptive speech enhancement Background noise Degradation Gain Perception. 

References

  1. 1.
    Boll SF (1979) Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans Acoust Speech, Signal Process ASSP-27:113–120Google Scholar
  2. 2.
    Ephraim Y, Malah D (1984) Speech enhancement using a minimum mean square error short-time spectral amplitude estimator. IEEE Trans Acoust Speech, Signal Process ASSP-32:1109–1121Google Scholar
  3. 3.
    Virag N (1999) Single channel speech enhancement based on masking properties of human auditory system. IEEE Trans Speech Audio Process 7:126–137CrossRefGoogle Scholar
  4. 4.
    Sauert B, Vary P (2006) Near end listening enhancement: speech intelligibility improvement in noisy environments, In: Proceedings of international conference on acoustics, speech, and, signal processing (ICASSP), pp 493–496Google Scholar
  5. 5.
    Sauert B, Enzner G, Vary P (2006) Near end listening enhancement with strict loudspeaker output power constraining. In: Proceedings of international workshop on acoustic echo and noise, control (IWAENC)Google Scholar
  6. 6.
    Sauert B, Vary P (2009) Near end listening enhancement optimized with respect to speech intelligibility index. In: Proceedings of european signal processing Conference (EUSIPCO) 17. EURASIP. Hindawi, New York, pp 1844–1848Google Scholar
  7. 7.
    Shin JW, Kim NS (2007) Perceptual reinforcement of the speech signal based on partial specific loudness. IEEE signal process lett 14(11):887–890CrossRefGoogle Scholar
  8. 8.
    Shin JW et al (2007) Speech reinforcement based on partial specific loudness. In: Proceedings of European conference on speech communication an technology (EUROSPEECH), pp 978–981Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Telecommunication EngineeringR.V. College of EngineeringBangaloreIndia
  2. 2.Department of Electronics and Communication EngineeringR.V. College of EngineeringBangaloreIndia

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