To improve the quality of noisy speech recordings, sound engineers have at their disposal a variety of signal processing techniques. These techniques often have a wide range of parameters which need to be adjusted to obtain optimal processing results. This paper investigates the difficulty of finding the best parameter settings for a commercial noise-reduction system. In a first experiment, operators adjusted the settings of a particular system while attempting to maximise the intelligibility of speech corrupted with babble noise at different signal-to-noise ratios. Their preferences were then evaluated in a listening experiment - showing that their chosen settings actually reduced intelligibility compared to the original signal. In another experiment a range of parameter settings for the same system were evaluated using both listeners and an intelligibility model based on a speech envelope distortion measure. Although the measure is imperfect, it is still able to predict optimal parameter settings better than the human operators.
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