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@article{188759,
        author = {Atharv Dadaso Kasture and Atul Ashok Kadam and Sujay Ashok Parmaj and Rohan Gampu Rathod and Pranaya Ashok Nalawade},
        title = {Portable Bilingual Translator},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {3288-3297},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188759},
        abstract = {Traditional voting methods, Traditional translation methods, such as mobile apps and basic handheld devices, still face problems like internet dependency, delayed processing, limited accuracy, and difficulty handling real-time speech. To address these issues, this paper presents a portable bilingual translator that utilizes offline speech recognition and translation models to enhance reliability. The system operates on an embedded Raspberry Pi setup, where Python-based modules manage speech processing in real time. An offline Vosk engine combined with Argos Translate safely handles speech input, converts it, and delivers results instantly through text and audio. Testing shows that the system can translate speech quickly, taking less than a few seconds per sentence while also maintaining consistent accuracy. Overall, the design is fast, dependable, and practical, making it suitable not only for everyday interactions but also for larger educational or field-use scenarios.},
        keywords = {Offline speech recognition, Embedded translation system, Raspberry Pi, Vosk, Argos, Speech-to-text, Speech-to-speech, Portable translator},
        month = {December},
        }