Design and Application of Neural Network-based Bp Algorithm in Speech Translation Robot

Abstract

The process of turning spoken words from one language into another's spoken words is called speech translation. It entails analyzing the spoken words and producing an accurate translation in real-time utilizing cutting-edge algorithms and machine learning approaches. The usage of speech translation technology is widespread across several sectors, including travel, business, and healthcare. For instance, a doctor who speaks English may utilize a voice translation system to converse with a patient who speaks other languages, and a corporate executive would do the same while speaking with associates or customers abroad. Nowadays speech translations are used in robots that are designed to translate speech from one language to another in real-time. in this paper, we implemented speech translation in the domain of intelligent science of medical care and technology. To assist English-speaking individuals in describing their symptoms to other language physicians or nurses, we suggested a neural network-based back propagation technique. Unlike laptops or tablets, a humanoid robot may be extended to reach out to individuals in need first and may eventually replace human labor. Finally, the neural-based control technique that was developed proved to be an efficient system for controlling human-robot voice translation, as judged both quantitatively and qualitatively. Results from a controlled trial demonstrating the translation's accuracy and success rate.