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Abstract The development of an ANN-based speech recognition system using MATLAB for controlling a humanoid robot prototype is presented in this research. Our proposed approach, therefore, will be in a good position to derive significant benefits from the powerful features and toolboxes in MATLAB in the areas of signal processing, machine learning, and robotics, way above most of the works available that have used platforms such as Arduino and Android with Bluetooth technology. The system is trained to recognize the five speech commands: "move forward," "move backward," "turn right," "turn left," and "stop." The custom GUI software has been developed to collect the data. It is processed by Fast Fourier Transform (FFT) and Mel-frequency cepstral coefficients (MFCC). After that, it goes through silence removal and normalized techniques with pre-processing ANN classifiers and integrated with the robot control system. The accuracy of the trained model on test data with multiple speakers is 87% and holds good for general purposes without being biased towards any specific speaker's voice characteristics. Developed prototype, hence, proves the feasibility and potential of MATLAB for the speech recognition task in control with humanoid robot and its applications in different domains like industries, healthcare, and defense. The modular architecture allows for easy customization and extension to incorporate additional voice commands and functionalities. Future research directions include improving robustness to noise, speaker-independent recognition, and integration with other modalities like gesture recognition and computer vision.
Shrivastava et al. (Wed,) studied this question.