Hinglish: The Language 600M+ Indians Speak and Why Your Voice AI Keeps Failing

Hinglish, a blend of Hindi and English, is spoken by over 600 million people in India and presents a significant challenge for monolingual automatic speech recognition (ASR) systems due to its code-switching nature. As the Indian internet user base continues to grow, with voice-based commands reaching 140 million users in 2024, the inability of standard speech recognition models to accurately process Hinglish poses a problem for businesses relying on voice AI. The article highlights the limitations of monolingual ASR models, which struggle with Hinglish's inter-sentential, intra-sentential, and intra-word code-switching patterns, leading to high word error rates. Multilingual models that can detect language shifts within an utterance are proposed as a solution, with features like word-level language detection and keyterm prompting for domain-specific vocabulary enhancing accuracy. Additionally, the article discusses the business implications of poor Hinglish recognition and the potential of multilingual models to cater to India's diverse and growing conversational AI market, emphasizing the importance of considering real-world audio conditions, accent variations, and compliance with data residency regulations.