The effects of noise reduction on cognitive effort in normal-hearing and hearing-impaired listeners

Authors

  • Anastasios Sarampalis University of California at Berkeley, Department of Psychology, 3210 Tolman Hall, Berkeley, CA 94702, USA
  • Sridhar Kalluri Starkey Hearing Research Center, 2150 Shattuck Ave, Berkeley, CA 94704, USA
  • Brent W. Edwards Starkey Hearing Research Center, 2150 Shattuck Ave, Berkeley, CA 94704, USA
  • Ervin R. Hafter University of California at Berkeley, Department of Psychology, 3210 Tolman Hall, Berkeley, CA 94702, USA

Abstract

A common complaint of hearing-impaired listeners is dif culty understanding speech in the presence of noise. Digital hearing aids have opened the door to complex signal processing algorithms that attempt to improve the quality, ease of listening, and/or intelligibility of speech in noisy environments. In reality, however, hearing aid users show no intelligibility improvements from single-microphone noise reduction (NR) algorithms, even though they sometimes report that speech sounds easier to understand. A possible explanation for this dichotomy is that NR algorithms replace a function that the human auditory system would otherwise perform. This redundancy means that there is no improvement in intelligibility, but a reduction in listening effort, since fewer cognitive resources would be necessary. We investigated this hypothesis using a dual-task paradigm with normal-hearing and hearing-impaired listeners. They were asked to repeat sentences or words presented in noise while performing either a memory or a reaction-time task. Our results showed that degrading speech by reducing the signal-to-noise ratio increased demand for cognitive resources, demonstrated as a drop in performance in the cognitive task. Use of a NR algorithm mitigated some of the deleterious effects of noise by reducing cognitive effort and improving performance in the competing task.

References

Bilger, R. C., Nuetzel, J. M., Rabinowitz, W. M., and Rzeczkowski, C. (1984). “Standardization of a Test of Speech-Perception in Noise” J. of Speech and Hear. Res. 27, 32-48.

Broadbent, D. E. (1958). “Perception and Communication,” Pergamon Press, London.

Ephraim, Y., and Malah, D. (1984). “Speech Enhancement Using a Minimum Mean-Square Error Short-Time Spectral Amplitude Estimator,” IEEE Transactions on Acoustics, Speech and Signal Processing 32, 1109-1121.

Ephraim, Y., and Malah, D. (1985). “Speech Enhancement Using a Minimum Mean- Square Error Log-Spectral Amplitude Estimator,” IEEE Transactions on Acoustics Speech and Signal Processing 33, 443-445.

IEEE (1969). “IEEE Recommended Practice for Speech Quality Measurements,” IEEE Transactions on Audio and Electroacoustics Au17, 225-246.

Kahneman, D. (1973). “Attention and Effort,” Prentice-Hall, New Jersey.

Lunner, T. (2003). “Cognitive function in relation to hearing aid use,” Intern. J. of Audiol. 42, S49-S58.

Pichora-Fuller, M. K., Schneider, B. A., and Daneman, M. (1995). “How Young and Old Adults Listen to and Remember Speech in Noise,” J. Acoust. Soc. of Am. 97, 593-608.

Additional Files

Published

2007-12-15

How to Cite

Sarampalis, A., Kalluri, S., Edwards, B. W., & Hafter, E. R. (2007). The effects of noise reduction on cognitive effort in normal-hearing and hearing-impaired listeners. Proceedings of the International Symposium on Auditory and Audiological Research, 1, 569–576. Retrieved from https://proceedings.isaar.eu/index.php/isaarproc/article/view/2007-57

Issue

Section

2007/6. Hearing-aid evaluation and optimization