Thai Voice-Controlled Analysis for Car Parking Assistance in System-on-Chip Architecture

Abstract

This paper introduces an analysis of Thai speech recognition for controlled car parking assist in the system-on-chip architecture. The objective is to investigate the male and female voice command signals, including Thai and English words, issued by the native Thai users. Hardware and software co-design by the Xilinx VIVADO are designed on an ARM multicore processor and a reconfigurable system on a ZYBO board. The experiments for Thai and English word recognition are conducted by using the Mel-frequency cepstral coefficient approach and presented in the form of spectrograms. The comparison of a voice command via Bluetooth and a reference command stored on an SD card and the ZYBO embedded board on a miniature electric vehicle is verified with the Pearson’s correlation coefficient (PCC). The experimental results show the accuracies of the received Thai/English, male/female, and indoor/outdoor voice commands as compared with the reference voice commands in the noisy surroundings. Hence, our system can support Thai/English and male/female voice commands to perform a set of actions for maneuvering a car by the PCC.

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“…Moreover, we have new models for Artificial Intelligence (AI) that can be perceived in different applications, such as voice recognition in vehicles(Prongnuch & Sitjongsataporn, 2020), recognition of traffic signs (Rodríguez et al, 2020; Calero et al, 2021), among others (Virgilio et al, 2020). As a plus, technological advances in hardware, in conjunction with these new AI models, have resulted in the development of new and hybrid algorithms, which seek the solution of different problems such as lighting (Mattoo et al, 2021), angles (Wijaya et al, 2020), real time (Benitez-Garcia et al, 2021), tracking (López-Monroy et al, 2021), among many others (Janai et al, 2020).…”