AI-Powered Video-to-Video Language Translation: English into Arabic by Integrating Speech Recognition, Neural Translation, and Audio Synthesis
Abstract:
In today’s connected world, breaking language barriers is key for effective communication. This paper introduces a new method for video-to-video language translation, focusing on converting English audio to Arabic using artificial intelligence (AI). The approach combines technologies like speech recognition, machine translation, and audio synthesis to create a smooth translation experience. The process starts with extracting audio from video files and splitting it into small, manageable parts based on pauses in speech. Each segment is transcribed using Google Speech Recognition to capture spoken words accurately. This text is then translated into Arabic using a neural translation model, which applies AI to ensure context and quality. Finally, the Arabic text is converted back to speech with text to-speech synthesis, creating an Arabic audio track ready to be added to the original video. This research shows how AI-powered tools can improve cross-language communication, providing a practical solution for content creators, educators, and audiences worldwide. Through real-world tests, the system’s effectiveness in accurate translation is confirmed, marking an important step for future developments in automated language translation.
