Automatic Speech Recognition and its Visual Perception Via a Cymatics Based Display

Qaisar, Saeed Mian; Alsharif, Hannan; Akbar, M.; Abdullah, Amnah A.

doi:10.1109/icaset.2019.8714297

Cited by 2 publications

(1 citation statement)

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“…For example, Yash Munoth used the tonoscope to convert English alphabet sounds into visible patterns using the principle of cymatics [4]. Saeed Mian Qaisar used a similar approach of cymatics to recognize isolated speech words [5]. However, although recent research results have shown promising potential, there is still need for a more accurate, reliable alternative approach that is easier to handle.…”

Section: Introductionmentioning

confidence: 99%

Cochlea-inspired sound visualization method

Park

Lee

Kim

2023

Nano-, Bio-, Info-Tech Sensors, and Wearable Systems 2023

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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.

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Section: Introductionmentioning

confidence: 99%