Authors : Jayapratha N; Vijaysurya M; Lingeshwaran G; Vema Naga Karish Gupta; Shivaprasanna

Volume/Issue : Volume 9 - 2024, Issue 11 - November

Google Scholar : https://tinyurl.com/26ez98fm

Scribd : https://tinyurl.com/ta6dp7eh

DOI : https://doi.org/10.38124/ijisrt/IJISRT24NOV1089

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This paper presents a novel approach to multilingual voice translation that integrates speech emotion recognition, multi-speaker differentiation, and voice cloning for cross-cultural applications. While existing translation systems achieve basic linguistic transformation, they often overlook critical elements like speaker-specific identity and emotional tone. The proposed system advances traditional models by leveraging deep learning to distinguish multiple speakers and recognize emotional states in multilingual contexts, preserving vocal nuances across languages. This study examines our model's architecture, evaluates its components, and assesses the potential impact on international communication, providing an innovative, culturally sensitive translation solution.

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