Evaluation of an auditory masked threshold noise suppression algorithm in normal-hearing and hearing-impaired listeners

  • Authors:
  • Kathryn Hoberg Arehart;John H. L. Hansen;Stephen Gallant;Laura Kalstein

  • Affiliations:
  • Department of Speech, Language and Hearing Sciences, Box 409 UCB, University of Colorado at Boulder, Boulder, CO;Department of Speech, Language and Hearing Sciences, Box 409 UCB, University of Colorado at Boulder, Boulder, CO and Robust Speech Processing Laboratory, Center for Spoken Language Research, Box 5 ...;Robust Speech Processing Laboratory, Center for Spoken Language Research, Box 594 UCB, University of Colorado at Boulder, Boulder, CO;Department of Speech, Language and Hearing Sciences, Box 409 UCB, University of Colorado at Boulder, Boulder, CO

  • Venue:
  • Speech Communication
  • Year:
  • 2003

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Abstract

While there have been numerous studies in the field of speech enhancement, the majority of these studies have focused on noise reduction for normal-hearing (NH) individuals. In addition, no speech enhancement algorithms reported in the signal processing community have reported an improvement in intelligibility, with the exception of a recent study by Tsoukalas et al. [IEEE Transactions of Speech and Audio Processing 5 (6) (1997) 497]. This study addresses the problem of speech enhancement for both NH and hearing-impaired (HI) subjects. A noise suppression algorithm based on auditory masked thresholds was implemented and evaluated for NH and HI subjects. Two different tests for intelligibility were used in the evaluation including the nonsense syllable test and the diagnostic rhyme test. Speech quality was evaluated using sentences from the hearing-in-noise test. Tests were performed using two types of noise (voice communications channel and automobile highway noise) at two different signal-to-noise ratios. Ten NH and 11 HI listeners were used to evaluate the enhancement algorithm. Results indicate that the enhancement algorithm yielded significantly better quality ratings and significantly better intelligibility scores in both NH and HI listeners in some but not all of the test conditions. The algorithm resulted in the greatest intelligibility improvements in the communications channels noise and for the nonsense syllable stimuli.