There are many industrial environments which are exposed to a high-level noise. It is necessary to protect people from the noise. Most of the time, the consumer requires a miniature version of a noise canceller to satisfy the internal working place requirements. Very important thing is to select the most appropriate personal hearing protection device, for example an earplug. It should guarantee high passive noise attenuation and allow for secondary sound generation in case of active control. In many cases the noise is nonstationary. For instance, some of the noisy devices are switched on and off, speed of some rotors or fans changes, etc. To avoid any severe transient acoustic effects due to potential convergence problems of adaptive systems, a fixed-parameter approach to control is appreciated. If the noise were stationary, it would be possible to design an optimal control filter minimising variance of the signal being the effect of the acoustic noise and the secondary sound interference. Because of noise nonstationarity for most applications, the idea of generalised disturbance defined by a frequency window of different types has been developed by the authors and announced in previous publications. The aim of this paper is to apply such an approach to different earplugs and verify its noise reduction properties. Simulation experiments are conducted based on real world measurements performed using the G. R. A. S. artificial head equipped with an artificial mechanical ear, and the noise recorded in a power plant.

There are many industrial environments which are exposed to a high-level noise, sometimes much higher than the level of speech. Verbal communication is then practically unfeasible. In order to increase the speech intelligibility, appropriate speech enhancement algorithms can be used. It is impossible to filter off the noise completely from the acquired signal by using a conventional filter, because of two reasons. First, the speech and the noise frequency contents are overlapping. Second, the noise properties are subject to change. The adaptive realisation of the Wiener-based approach can be, however, applied. Two structures are possible. One is the line enhancer, where the predictive realisation of the Wiener approach is used. The benefit of using this structure it that it does not require additional apparatus. The second structure takes advantage of the high level of noise. Under such condition, placing another microphone, even close to the primary one, can provide a reference signal well correlated with the noise disturbing the speech and lacking the information about the speech. Then, the classical Wiener filter can be used, to produce an estimate of the noise based on the reference signal. That noise estimate can be then subtracted from the disturbed speech. Both algorithms are verified, based on the data obtained from the real industrial environment. For laboratory experiments the G. R. A. S. artificial head and two microphones, one at back side of an earplug and another at the mouth are used.