Text-to-Speech Rest API

Provides a synchronous REST endpoint where a POST request with text returns base64-encoded audio as response.

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import base64
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combined = "".join(response.audios)
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wav_bytes = base64.b64decode(combined)
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with open("output.wav", "wb") as f:
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    f.write(wav_bytes)

Common use cases:

• Story narration — Generate expressive audio for audiobooks and narratives
• Podcast generation — Create natural-sounding voiceovers for episodes at scale
• Content creation — Add voice to blogs, articles, and social media posts
• E-learning — Build multilingual course material with clear pronunciation

What You Can Do

Model: Bulbul v3

Bulbul v3 is purpose-built for Indian languages and accents. It handles code-mixed text (e.g., Hinglish), number normalization, and natural prosody out of the box — with minimal preprocessing needed.

Text to Speech Features

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from sarvamai import SarvamAI
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from sarvamai.play import save
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client = SarvamAI(api_subscription_key="YOUR_SARVAM_API_KEY")
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# Convert text to speech
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audio = client.text_to_speech.convert(
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    target_language_code="en-IN",
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    text="Welcome to Sarvam AI!",
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    model="bulbul:v3",
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    speaker="shubh"
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)
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save(audio, "output1.wav")

API Response Format

Supported audio formats: WAV (default), MP3, Linear16, Mulaw, Alaw, Opus, FLAC, AAC

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{
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  "request_id": "20241115_12345678-1234-5678-1234-567812345678",
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  "audios": [
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    "UklGRiQAAABXQVZFZm10IBAAAAABAAEAQB8AAAB9AAACABAAZGF0YQAAAAA..."
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  ]
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}

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import base64
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audio_base64 = response.audios[0]
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audio_bytes = base64.b64decode(audio_base64)
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with open("output.wav", "wb") as f:
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    f.write(audio_bytes)

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import fs from "fs";
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const audioBase64 = response.audios[0];
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const audioBuffer = Buffer.from(audioBase64, 'base64');
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fs.writeFileSync('output.wav', audioBuffer);

Error Responses

All errors return a JSON object with an error field containing details about what went wrong.

Error Response Structure

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{
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  "error": {
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    "message": "Human-readable error description",
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    "code": "error_code_for_programmatic_handling",
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    "request_id": "unique_request_identifier"
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  }
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}

Error Codes Reference

Example Error Response

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{
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  "error": {
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    "message": "Text exceeds maximum length of 1500 characters for bulbul:v3",
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    "code": "unprocessable_entity_error",
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    "request_id": "20241115_abc12345"
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  }
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}

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from sarvamai import SarvamAI
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from sarvamai.core.api_error import ApiError
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client = SarvamAI(api_subscription_key="YOUR_SARVAM_API_KEY")
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try:
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    response = client.text_to_speech.convert(
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        text="Welcome to Sarvam AI!",
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        target_language_code="en-IN",
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        speaker="shubh",
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        model="bulbul:v3"
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    )
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    # Process audio...
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except ApiError as e:
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    if e.status_code == 400:
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        print(f"Bad request: {e.body}")
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    elif e.status_code == 403:
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        print("Invalid API key. Check your credentials.")
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    elif e.status_code == 422:
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        print(f"Invalid parameters: {e.body}")
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    elif e.status_code == 429:
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        print("Rate limit exceeded. Wait and retry.")
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    else:
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        print(f"Error {e.status_code}: {e.body}")