Tackling the Problem of Multilingualism in Voice Assistants
Soham Sabharwal, Rohan Sahni · International Journal of Electrical Electronics and Computers · 2024
Voice assistants like Alexa and Siri have become increasingly advanced due to improvements in AI and language processing models like GPT and Gemini. However, these systems often perform poorly with less commonly spoken languages, such as many Indian languages, creating a significant accessibility gap. This paper addresses the problem of multilingualism in voice assistants, with a focus on languages like Hindi, Punjabi, and Bengali. We examine the evolution of voice assistants and highlight the major technical challenges they face, including speech recognition, language processing, and response generation in low-resource languages. To overcome these barriers, we propose a novel framework that combines different AI models to enhance multilingual support. Our approach offers a potential solution to make voice assistants more inclusive and accessible for speakers of underrepresented languages. By broadening language support, this research has the potential to extend the benefits of AI to a much wider audience.