Predictive measures of the intelligibility of speech processed by noise reduction algorithms

Authors

  • Karolina Smeds Widex A/S, ORCA Europe, Stockholm, Sweden
  • Florian Wolters Widex A/S, ORCA Europe, Stockholm, Sweden; Univeristy of Applied Sciences, Oldenburg, Germany
  • Arne Leijon KTH, Stockholm, Sweden
  • Sara Båsjö Widex A/S, ORCA Europe, Stockholm, Sweden
  • Sofia Hertzman Widex A/S, ORCA Europe, Stockholm, Sweden

Abstract

A number of predictive measures were evaluated in terms of their ability to predict the effect on speech intelligibility of different types of noise reduc- tion (NR). Twenty listeners with hearing impairment and ten listeners with normal hearing participated in a blinded laboratory study. An adaptive speech test was used. The speech test produce results in terms of physical signal-to-noise ratios that correspond to equal speech recognition perfor- mance with and without the NR algorithms, which facilitates a direct statis- tical test of how well the predictive measures agree with the experimental results. Three NR algorithms and a reference condition were compared. The experimental results were used to evaluate a number of predictive measures, including a standard Speech Intelligibility Index (SII) method, two time- variable SII methods, and one coherence-based SII method. Further, one measure based on the correlation between band envelope magnitudes of clean and processed noisy speech was evaluated. The measures that make short-time analyses of both speech and noise did best in the comparison.

References

ANSI-S3.5 (1997). American national standard methods for the calculation of the speech intelligibility index. New York: Am National Standards Institute.

Byrne, D., and Dillon, H. (1986). "The National Acoustic Laboratories' (NAL) new procedure for selecting the gain and frequency response of a hearing aid" Ear Hear., 7, 257-265.

Hagerman, B. (1982). "Sentences for testing speech intelligibility in noise" Scand. Audiol., 11, 79-87.

Hagerman, B., and Olofsson, Å. (2004). "A method to measure the effect of noise reduction algorithms using simultaneous speech and noise" Acta Acustica, united with Acustica, 90, 356-361.

Holube, I., Fredelake, S., Vlaming, M., and Kollmeier, B. (2010). "Development and analysis of an International Speech Test Signal (ISTS)" Int. J. Audiol., 49, 891-903.

Kates, J. M., and Arehart, K. H. (2005). "Coherence and the speech intelligibility index" J. Acoust. Soc. Am., 117, 2224-2237.

Loizou, P.C. (2007). Speech enhancement theory and practice. Boca Raton, FL, USA: Taylor & Francis Group.

Luts H., Eneman K., Wouters J., Schulte M., Vormann M., Büchler M., et al. (2010). "Multicenter evaluation of signal enhancement algorithms for hearing aids" J. Acoust. Soc. Am., 127, 1491-1505.

Pavlovic, C. V., Studebaker, G. A., and Sherbecoe, R. L. (1986). "An articulation index based procedure for predicting the speech recognition performance of hearing-impaired individuals" J. Acoust. Soc. Am., 80, 50-57.

Rhebergen, K. S. and Versfeld, N. J. (2005). "A Speech Intelligibility Index-based approach to predict the speech reception threshold for sentences in fluctua- ting noise for normal-hearing listeners" J. Acoust. Soc. Am., 117, 2181-2192.

Smeds, K., Bergman, N., Hertzman, S. and Nyman, T. (2009). "Noise reduction in modern hearing aids – Long-term average gain measurements using speech" in Proceedings of The International Symposium on Auditory and Audio- logical Research (ISAAR). Binaural processing and spatial hearing. Helsingør, Denmark. Edited by J. M. Buchholz, T. Dau, J. C. Dalsgaard and T. Poulsen, pp. 445-452.

Smeds, K., Wolters, F., Nilsson, A., Båsjö, S., Hertzman, S. and Leijon A. (2010). "Objective measures to quantify the perceptual effects of noise reduction in hearing aids" in Proceedings of The AES 38th International Conference - Sound quality evaluation. Audio Engineering Society, Piteå, Sweden. Edited by J. Vanderkooy, pp. 101-107.

Taal, C. H., Hendriks, R. C., Heusdens, R., and Jensen, J. (2010). "A short-time objective intelligibility measure for time-frequency weighted noisy speech" in Proceedings of ICASSP 2010, pp. 4214-4217.

Additional Files

Published

2011-12-15

How to Cite

Smeds, K., Wolters, F., Leijon, A., Båsjö, S., & Hertzman, S. (2011). Predictive measures of the intelligibility of speech processed by noise reduction algorithms. Proceedings of the International Symposium on Auditory and Audiological Research, 3, 355–362. Retrieved from https://proceedings.isaar.eu/index.php/isaarproc/article/view/2011-41

Issue

Vol. 3 (2011): Speech Perception and Auditory Disorders

Section

2011/3. Models of speech processing and perception

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