Abstract

This study focuses on noise evaluation and targeted noise reduction efforts. Goals of this study are to propose a noise annoyance evaluation (D) by developing the auditory saliency model. D replaces complex subjective measurements with concrete objective values. This noise evaluation method improves the accuracy of sound quality evaluation by avoiding the bias caused by different emphasis in traditional noise evaluation schemes and the huge workload caused by using questionnaires. Whether it is equipment operation noise or environmental noise, analyzing the noise frequency structure is an important part of achieving targeted noise reduction. Through the EA model (Early Acoustic Model), which is more suitable for the actual working conditions of the human ear, this study has combined with the energy algorithm to establish the noise annoyance factor (BP), which can accurately identify the main frequencies in the noise signal that affect the sound quality. Meanwhile, they also have a vital role in analyzing the frequency structure of the movement. This research verifies the accuracy of noise annoyance evaluation (D) by analyzing the simulation signal, vacuum cleaner working signal, and fan heat dissipation signal. The noise annoyance factor (BP) is used to locate the center frequency range of a group of acoustic signals that produce the most significant noise annoyance to achieve the purpose of targeted noise reduction. This study provided a new solution for sound quality evaluation and targeted noise reduction.

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