Building an AI Hindi Tutor: A Journey from Family Dinner to Full-Stack Application

It all started with a family dinner conversation. My nephew, growing up in Singapore, was struggling to maintain his Hindi language skills in an environment where Chinese was the predominant language among his peers. This challenge resonated with me — why should geographic location limit a child’s ability to practice their heritage language? That dinner conversation sparked an idea: what if we could create an always-available Hindi conversation partner using AI?

The Vision

The goal was simple yet ambitious: build a mobile-first application that would serve as a 24/7 Hindi language companion for children aged 4–8. Unlike traditional language learning apps that focus on structured lessons, I wanted to create something that mimicked natural conversation — just like chatting with a friend. The key was to make it engaging enough for children while helping them improve their Hindi speaking skills.

Technical Architecture and Decisions

Speech-to-Text: The Foundation
For speech recognition, I chose the Sarvam API, specifically because it’s trained on Hindi audio. While exploring options, I initially tested the Chromium-based speech-to-text API, but it struggled with a crucial aspect of children’s speech patterns: the long pauses between words that are typical when someone isn’t fluent. Sarvam’s approach of processing complete audio files rather than real-time streaming proved more robust for handling these natural hesitations.

Text-to-Speech: Making it Engaging
The choice between Sarvam and ElevenLabs for text-to-speech presented an interesting tradeoff. While Sarvam offered speed control (crucial for language learning), I ultimately chose ElevenLabs for its superior voice quality and emotional range. The ability to convey excitement in questions and express various intonations made the interaction feel more natural and engaging. This decision prioritized user engagement over technical perfection — a choice that aligned with my goal of keeping children interested.

The Brain: GPT-4 Integration
The conversational logic is powered by GPT-4, with a carefully crafted prompt that instructs the AI to “be like a mother who is curious about their child.” This prompt engineering ensures responses that are age-appropriate while maintaining natural conversation flow. The system doesn’t force topics or follow a rigid curriculum — instead, it lets children lead the conversation wherever their interests take them, whether that’s school, dinosaurs, or their favorite cartoons.

Error Correction and Gamification
Rather than interrupting the flow with constant corrections, the system specifically focuses on catching English-Hindi code-switching (for example, when a child says “मैं school जा रहा हूं” instead of “मैं विद्यालय जा रहा हूं”). These corrections are presented gently, maintaining the child’s confidence. To keep engagement high, I implemented a point system with visual rewards — including animations of Captain America’s shield, a universally recognizable symbol of achievement.

Technical Challenges and Solutions

One of the main challenges was the recording interface. While voice activity detection would have been ideal, I opted for a manual recording button with visual cues (an animated microphone) to ensure accuracy in speech capture. This decision was informed by studying other language learning apps and prioritizing reliable speech recognition over interface smoothness.

The application is hosted on Heroku and designed to be mobile-first, recognizing that most users would access it via smartphones. The frontend initiates conversation with an open-ended prompt about the user’s day, setting a casual tone that encourages natural dialogue.

Future Developments:

While the current version serves its core purpose, several exciting possibilities for expansion exist:

1. Age-specific response modeling using different GPT prompts based on the user’s age
2. A dedicated module for practicing challenging Hindi phonemes
3. Integration of Indian cultural elements and festivals into conversations
4. A parent mode for sharing conversation transcripts, enabling families to continue discussions offline
5. Analytics to track engagement patterns and optimize the reward system

Looking Forward

What started as a solution for one child in Singapore has the potential to help the entire Indian diaspora maintain their connection with Hindi. As more families move globally, tools like this could play a crucial role in preserving language skills and cultural connections across generations.

The future roadmap includes making the system more robust for various accents and potentially expanding to other Indian languages. But the core principle will remain the same: creating a safe, engaging space for children to practice their heritage language, one conversation at a time.

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This project was built using Sarvam API for STT, ElevenLabs for TTS, GPT-4 for conversation logic, and is hosted on Heroku. The frontend is designed to be mobile-first with engaging animations and a child-friendly interface.