Published Paper Details:

Effective communication in a globalized world is increasingly challenged by accent variations within the same language. Despite significant advancements in multilingual speech translation technologies, the specific domain of intra-language accent translation remains largely unexplored, creating barriers to understanding in critical contexts such as international business meetings, virtual classrooms, and customer service interactions. Existing systems primarily focus on translating speech between different languages and often overlook the nuanced differences that accents can introduce . This research addresses this critical gap by proposing a real-time accent translation system designed to enhance comprehension and communication efficiency across diverse accents within a single language. The proposed system consists of three core modules: Accent Detection and Classification, Accent Translation, and Speech Synthesis. Utilizing advanced machine learning techniques, particularly deep learning models for accurate accent detection and generative adversarial networks (GANs) for effective accent translation, the system preserves the original linguistic content while adapting phonetic features to align with the desired accent. The approach is data-driven, relying on diverse datasets that encompass various accents to ensure robust performance in real-world applications. Preliminary results indicate that the system achieves high accuracy in accent detection and maintains a latency of less than 200 milliseconds, making it suitable for real-time communication scenarios. By addressing the challenges posed by accent differences, this research not only contributes to the field of speech processing technology but also promotes inclusivity and understanding in global communication settings. The findings suggest that the proposed solution has significant implications for industries such as education, customer service, and international business, paving the way for more effective interactions in linguistically diverse environments. In conclusion, this research establishes a foundational framework for real-time accent translation, highlighting its potential to bridge communication gaps and enhance cross-cultural understanding in an increasingly interconnected world.