AI-Powered Real-Time Multilingual Speech Translation with Voice Cloning

Language diversity poses a significant challenge in effective communication across global platforms, especially in digital and multimedia environments. Automated speech translation systems have become essential to overcome these barriers and enable seamless information exchange. This paper presents an AI-powered real-time multilingual speech translation system that processes uploaded audio files to generate accurate speech transcription and language translation in near real time. The proposed system utilizes automatic speech recognition to convert spoken audio into text, followed by neural machine translation to translate the transcribed content into a target language. In addition, basic audio content analysis, including summarization and virality assessment, is performed to extract meaningful insights from the input audio. The system demonstrates efficient processing with minimal delay between input and output, making it suitable for practical multilingual applications. This work represents the first module of a larger project aimed at real-time multilingual speech translation and advanced speech synthesis. Experimental results show that the system provides reliable transcription, effective translation, and useful content analysis for multilingual audio data.