Leveraging AWS Rekognition, Translate, and Polly for Multilingual Image-to-Text Translation and Speech Synthesis

Using AWS Rekognition, Translate, and Polly: Multilingual Image-to-Text Translation and Speech Synthesis Abstract Over the last decade, cloud-based artificial intelligence services have changed the way data is interacted with, providing scalable solutions to complex tasks and indeed reaching from image recognition to text translation or text-to-speech synthesis. This paper presents an innovative system that is powered by three Amazon Web Services: AWS Rekognition, AWS Translate, and AWS Polly, fully integrated within a unified pipeline that allows for extraction from image to text, multilingual translation, and also synthesis of speech from texts. The objectives of this system are as follows: extracting text from images, translating it into a language that he prefers, and finally converting the translated text into words. This will enable tremendous real-world applications, including providing information to the blind, translation of documents in multiple languages, and further enrichment in interactive customer services. This entire process is automated and optimized by bringing these AWS services together, thus reducing human intervention to a great extent. Our testing reveals that the system accurately identifies printed as well as handwritten content, does high-accuracy translation, and generates quality speech in multiple languages. This system is scalable, accurate, and real time. It finds applications across various industries. The base of this research opens pathways for using the powerful AI tools in AWS to build automated, multilingual, and accessible solutions.