Functional magnetic resonance imaging (fMRI) has become the method of choice for studying the neural correlates of cognitive tasks. Nevertheless, the scanner produces acoustic noise during the image acquisition process, which is a problem in the study of auditory pathway and language generally. The scanner acoustic noise not only produces activation in brain regions involved in auditory processing, but also interferes with the stimulus presentation. Several strategies can be used to address this problem, including modifications of hardware and software. Although reduction of the source of the acoustic noise would be ideal, substantial hardware modifications to the current base of installed MRI systems would be required. Therefore, the most common strategy employed to minimize the problem involves software modifications. In this work we consider three main types of acquisitions: compressed, partially silent, and silent. For each implementation, paradigms using block and event-related designs are assessed. We also provide new data, using a silent event-related (SER) design, which demonstrate higher blood oxygen level-dependent (BOLD) response to a simple auditory cue when compared to a conventional image acquisition.