AI-Driven Voice Translator for Cross-Language Communication

Speech translation system that translates in real-time, eradicating linguistic barriers but keeping the emotional context intact within the spoken language. The existing systems are using ASR algorithms, NMT, and TTS algorithms to decode the speech, which sometimes fail to capture finer details of emotions. Our solution uses CTC, GRU, and Parallel WaveGAN. CTC improves recognition accuracy by handling variable- length speech effectively without explicit alignment. Accordingly, GRU improves translation quality and contextual meaning while Parallel WaveGAN offers high-quality speech synthesis with natural expression.