A digital pattern playback system implemented in Python

Abstract

Pattern playback systems were instrumental in speech perception research [e.g., Cooper et al. (1951)] and can be valuable for pedagogical purposes [e.g., Arai et al. (2006)]. They would be utilized further if one could integrate them with other speech processing software written in a common programming language. In response, I present an open-source digital pattern playback system implemented in the Python programming language. The software allows the user to provide an image of a magnitude spectrogram as input by either selecting an image file (e.g., PNG, JPG) or drawing one directly on a blank canvas using a pointing device (e.g., computer mouse, stylus, fingertip). It first translates pixel values of the image to an array of magnitude spectral coefficients and then applies the inverse short-time Fourier transform assuming zero phase to convert the array into a waveform. Users can readily manipulate basic parameters of conversion (e.g., sampling rate, frame length) and augment the process by utilizing various signal processing methods available in Python libraries such as SciPy and librosa. The source code is available for download and will be maintained on the author's GitHub repository and personal website.