Hinglish Speech-to-Text API: Setup Guide for Voice AI (2026)

Dhiraj·26 June 2026·Updated 26 June 2026

Founder of Bolti, writing about voice AI for Indian businesses.

Bolti, a voice AI platform for building production-ready conversational phone agents, provides sub-second latency and native support for multilingual conversations, including mixed-language inputs. If you are building voice agents for the Indian market, you cannot rely on standard single-language models. Your callers will naturally speak Hinglish—a fluid blend of Hindi and English. Handling this requires a robust hinglish speech to text api strategy that can process rapid language switches without dropping calls or losing context.

You can start building with Bolti today using our pricing details starting at just ₹6/minute pay-as-you-go, or explore the platform with a 50-minute free trial.

What is a hinglish speech to text api and why do you need it?

A hinglish speech-to-text API is a speech recognition system trained specifically to transcribe mixed Hindi and English speech spoken in natural, conversational Indian accents. Without it, standard speech-to-text engines fail to recognize mixed phrases, leading to high word-error rates and broken voice AI experiences.

In India, people rarely stick to one language on a phone call. A customer checking their order status might say:

"Mera order deliver kab hoga?" (When will my order be delivered?)
"Mujhe refund chahiye because product damaged tha." (I want a refund because the product was damaged.)
"Billing address change karna hai, please help." (I need to change my billing address, please help.)

If your voice agent uses a strict English-only or Hindi-only speech-to-text engine, it will misinterpret these blended phrases. The result is a frustrated customer and a failed call. Bolti solves this by integrating advanced, multilingual speech recognition that natively understands Hinglish, Marathi-English, Tamil-English, and over 80 other global languages.

How to configure Hinglish speech-to-text on phone calls

Setting up Hinglish speech-to-text on Bolti does not require complex machine learning code. You can configure your agent's language settings directly in the dashboard or via the API.

Step 1: Select your multilingual engine

When creating your agent in the Bolti dashboard, navigate to the Agent Settings. Under the Languages section, select the multilingual model that supports Indian English and Hindi dialect blending. This ensures the speech-to-text engine expects code-switching (the technical term for mixing languages) and transcribes both scripts accurately into a unified text format.

Step 2: Write your system prompt to accept Hinglish

The LLM powering your voice agent needs to understand how to respond to Hinglish. If your system prompt forces the LLM to reply only in formal English, the conversation will feel robotic.

Use a prompt like this to align the LLM's behavior:

"You are a helpful customer support assistant for an Indian e-commerce company. The user will speak to you in a mix of Hindi and English (Hinglish). Respond in a natural, conversational Hinglish style using Latin script (e.g., write 'shipped ho gaya hai' instead of 'यह भेज दिया गया है' or 'it has been shipped'). Keep your sentences short and direct."

Step 3: Connect your backend APIs using Workspace HTTP Tools

Once the hinglish speech to text api transcribes the caller's intent, your agent needs to take action. This is where Bolti's introduction to tool calling comes into play. A voice agent with tools is an employee—it can query databases, update CRM records, or process refunds in real time.

To connect your database:

Go to Dashboard → Tools in the left navigation.
Click New Tool to configure a workspace HTTP tool.
Set your Tool Name (e.g., check_order_status) and write a clear description. The LLM uses this description to decide when to call the tool.
Input your Endpoint URL and select your Request Method (like POST or GET).
Set up authentication (such as Bearer Token or API Key Header) and save.

During a live Hinglish call, if the user says, "Mera order status check karo," the STT engine transcribes the Hinglish text, the LLM recognizes the intent, and immediately triggers your check_order_status API.

Key challenges in Hinglish speech recognition (and how to solve them)

Challenge	Why it happens	How Bolti handles it
Acoustic Noise	Many calls in India are made from noisy streets, markets, or moving vehicles.	Bolti uses telephony-grade noise cancellation to isolate the speaker's voice before processing it through the STT engine.
Script Confusion	Some engines try to output Devanagari script for Hindi words and Latin script for English words in the same sentence.	Bolti's recommended multilingual configurations output a clean, unified Latin-script transcription, making it easy for the LLM to process.
Accent Variations	India has diverse regional accents that affect how both English and Hindi words are pronounced.	Our speech models are trained on diverse Indian telephonic datasets, ensuring high accuracy across regional accents.

Developer workflows: Managing agents via MCP

If you prefer working in your code editor rather than clicking through dashboards, Bolti provides a native Model Context Protocol (MCP) server.

Using Cursor or Claude Desktop, you can manage your Hinglish-enabled voice agents directly from your terminal or chat interface. You can instruct your editor to:

"List all active agents and show their configured languages."
"Create a new tool called verify_pincode and assign it to my Hinglish delivery agent."
"Pull the transcript of the last Hinglish support call that lasted more than 3 minutes to check STT accuracy."

This workflow allows developers to rapidly iterate on prompt engineering and tool definitions without leaving their development environment.

Security and data protection for Indian voice data

Handling customer calls in India means complying with local regulations like the Digital Personal Data Protection (DPDP) Act. Voice agents process highly sensitive information, such as phone numbers, addresses, and payment details.

Bolti is built with strict security controls. All call recordings live in private, encrypted object storage, accessible only via time-limited signed URLs. Active call sessions are completely isolated, and application logs are scrubbed of sensitive credentials. For enterprise customers with strict compliance needs, Bolti offers PII redaction at runtime, ensuring sensitive data is masked before it ever reaches third-party LLM providers.

Set up your first Hinglish voice agent

Build a production-ready voice agent that understands Hinglish, processes tool calls, and handles interruptions with sub-second latency. With Bolti, you get ₹6/minute pay-as-you-go pricing and your first 50 minutes are completely free.

Frequently Asked Questions

Does the Hinglish speech-to-text API transcribe into Devanagari or Latin script?

By default, Bolti's recommended multilingual configurations transcribe Hinglish speech into Latin script (e.g., 'mera order status check karo'). This makes it significantly easier for standard Large Language Models to read, comprehend, and respond to the text accurately.

Can I use my own telephony provider with Bolti?

Yes. Bolti supports Bring Your Own Carrier (BYOC). You can connect your existing SIP trunks from providers like Twilio, Plivo, or Exotel, or you can purchase and use virtual phone numbers directly through the Bolti platform.

How does Bolti handle interruptions during a call?

Bolti is built specifically for real-time phone conversations. It features sub-second turn-taking and advanced interruption handling. If a caller speaks while the agent is talking, the agent stops immediately, listens to the user, and processes the new input.

Does Bolti store my customers' private call data?

Call recordings are stored securely in private, encrypted object storage and are only accessible via time-limited signed URLs. For highly sensitive use cases, Bolti offers enterprise features like PII redaction at runtime to mask sensitive data before it reaches external LLM APIs.