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Lars Bramsløw

Research Engineer, PhD, Project Leader

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mail@eriksholm.com

The signals entering a hearing-aid are affected by compression amplification in various ways, not all of which are part of the theoretical basis for providing compression. These side effects need to be understood and minimised in future hearing-aid systems.

Background

Compression (non-linear amplification) is an almost universal feature of modern hearing aids. It comes in many different forms, and is provided for a range of different reasons. The different functions of compression cannot easily be reconciled in one hearing-aid system. Thus, all currently known compression systems provide both a desired performance and some undesired (or at least uncontrolled) side effects.

We are endeavouring to develop methods for quantifying such side effects; preferably objective measurement techniques based on examination of the signals entering and leaving a hearing-aid system. Validation of such objective measures clearly requires perceptual experiments involving listeners with impaired and/or normal hearing. At present we are focusing on speech intelligibility and studying the side effects of compression when the desired speech is present against a background of noise. Variables of interest include the Signal-Noise Ratio (SNR), modulation characteristics of the noise, and parameters of the compression system in question.

Methods

For this kind of work, we need to examine how the speech signal itself is modified by the presence of the noise signal in the hearing aid, so it is highly desirable to have separate access to speech and noise signals - both at the input and output of the hearing aid. In the laboratory, input signals are generally available separately, but the output is a mixture. We decompose this mixture using the method of Hagerman and Olofsson1. Having done this, we may derive many indices describing the distortion of either the speech or the noise, or describing how the mixture changes from input to output. We can then apply methods for predicting the intelligibility of a given mixture of speech and noise.

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Results

A fundamental quantity to measure is the long-term RMS level of the speech and noise signals. The ratio between these (SNR) is not necessarily the same at the output as it is at the input of the compressor. As an example, Figure 1 shows the relationship between Input SNR and Output SNR for a fast-acting compressor, when the noise is highly modulated. It can be seen that the Output SNR may be either lower or higher than the Input SNR, dependent on the Input SNR itself. The change in long-term SNR through the system may be several dB in either direction.

It is natural to ask whether objective effects of the type seen in Figure 1 are reflected in the speech intelligibility performance of real listeners. To test this, we carried out a listening experiment with twelve hearing-impaired subjects. Seven different conditions were constructed, such that the long-term SNR at the ear (Output SNR) varied systematically as a combination of variations in Input SNR and variations of compression system parameters. We found that a given alteration in Output SNR caused by compression leads to a change in listener performance similar to that which occurs if the Input SNR (in a linear hearing aid) is altered by the same amount.

Further work has investigated the utility of various alternative indices for predicting the intelligibility changes observed in the abovementioned listening tests. So far, the Extended Speech Intelligibility Index (ESII)2 seems to be an excellent candidate.

Conclusions

The results of these experiments have implications for the robust design of studies aiming to compare the benefits of alternative compression systems in hearing aids. It is vital to maintain control over the SNR at which testing takes place, or at least to verify that the systems being compared do not change their behaviour substantially across the range of SNRs which may occur.


Further reading

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

2 Rhebergen KS, Versfeld NJ, Dreschler WA. (2006) Extended speech intelligibility index for the prediction of the speech reception threshold in fluctuating noise. Journal of the Acoustical Society of America, 120(6), p. 3988-3997.

Naylor, G, Johannesson, RB. (2009) Long-Term Signal-to-Noise Ratio at the Input and Output of Amplitude-Compression Systems. J Am Acad Audiol 20:161-171.

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    Poster

    Perceptual correlates of the long-term SNR change caused by fast-acting compression