This study presents the initial study for a new approach to visualize an acoustic sound aimed at mimicking the traveling wave propagation of the basilar membrane within the human cochlea. Typically, a fast Fourier transform (FFT) is required to extract the frequency information from acoustic sound (i.e., voice) for speech recognition. Although this algorithm ensures real-time frequency extraction due to the inherent fast recursive structure, it is necessary to develop a new frequency selectivity technique for advanced speech recognition. We explore the potential of the cochlea-inspired sound visualization to deliver new frequency selectivity by using an image sensor. The experimental prototyping model is fabricated, and we capture images of frequency dependent wave propagation motion using a camera and reproduce 2D images through motion magnification. This approach offers a promising application for speech recognition systems because no FFT is required to extract the frequency information, although there are outstanding technical problems that need to be further examined.
KEYWORDS: Visualization, Edge detection, Ultraviolet radiation, Speech recognition, Composites, Particles, Digital cameras, Detection and tracking algorithms, Scanning electron microscopy, RGB color model
This preliminary study presents a sound wave visualization method using mechanoluminescent composite diaphragms made of mechanoluminescence particles (SAO). To visualize the acoustic wave, the concept of Cymatics is used to make the sound waves and vibrations observable (the human sense of vision), as it is the most discriminating human sense. The goal of this study is eventually to extract the frequency information from images captured by compact image sensors without fast Fourier transform (FFT) whereas most previous studies on sound visualization focus on a technique used to enhance the understanding of acoustical behaviors, such as reflection, diffraction, and interference. In this study, highly pressure-sensitive mechanoluminescent diaphragms will be fabricated and used to produce the images in response to audible sound excitation such as speech. This initial study will offer the potential application for new means of speech recognition principle because a systematic visual perception of the isolated speech words can be achieved using the proposed sound visualization method.
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