| name | speech-to-text |
| description | Transcribe audio to text using Sarvam AI's Saaras model. Handles speech recognition, transcription, and voice interfaces for 23 Indian languages. Supports 5 output modes, auto language detection, WebSocket streaming, and batch diarization. Use when converting speech to text or building voice-enabled apps. |
| license | Apache-2.0 |
| metadata | {"author":"sarvam-ai","version":"3.0"} |
Speech-to-Text — Saaras
[!IMPORTANT]
Auth: api-subscription-key header — NOT Authorization: Bearer. Base URL: https://api.sarvam.ai/v1
Model
saaras:v3 — 23 languages, 5 output modes (transcribe, translate, verbatim, translit, codemix), auto language detection.
Quick Start (Python)
from sarvamai import SarvamAI
client = SarvamAI()
response = client.speech_to_text.transcribe(
file=open("audio.wav", "rb"),
model="saaras:v3",
mode="transcribe"
)
print(response.transcript)
Quick Start (JavaScript/TypeScript)
import { SarvamAIClient } from "sarvamai";
import * as fs from "fs";
const client = new SarvamAIClient({ apiSubscriptionKey: "YOUR_SARVAM_API_KEY" });
const response = await client.speechToText.transcribe({
file: fs.createReadStream("audio.wav"),
model: "saaras:v3",
mode: "transcribe"
});
console.log(response.transcript);
Batch API (Long Audio + Diarization)
job = client.speech_to_text_job.create_job(
model="saaras:v3",
mode="transcribe",
language_code="hi-IN",
with_diarization=True,
num_speakers=2
)
job.upload_files(file_paths=["meeting.mp3"])
job.start()
job.wait_until_complete()
job.download_outputs(output_dir="./output")
Supports audio up to 1 hour, up to 8 speakers, all 5 output modes.
WebSocket Streaming
import asyncio, base64
from sarvamai import AsyncSarvamAI
async def stream_audio():
client = AsyncSarvamAI()
async with client.speech_to_text_streaming.connect(
model="saaras:v3",
high_vad_sensitivity=True,
flush_signal=True
) as ws:
with open("audio.wav", "rb") as f:
audio_base64 = base64.b64encode(f.read()).decode("utf-8")
await ws.transcribe(audio=audio_base64, encoding="audio/wav", sample_rate=16000)
await ws.flush()
response = await ws.recv()
print(response)
asyncio.run(stream_audio())
Supports sessions up to 8 hours. Use sample_rate=8000 for telephony audio.
Gotchas
| Gotcha | Detail |
|---|
| REST: 30s limit | Audio >30s fails. Use Batch API or WebSocket for longer files. |
| JS method name | client.speechToText.transcribe({...}) — camelCase, NOT speech_to_text. File via fs.createReadStream(). |
| WebSocket codecs | Only wav, pcm_s16le, pcm_l16, pcm_raw. MP3/AAC/OGG NOT supported for streaming. |
| WebSocket audio | Must be base64-encoded. Use sample_rate=8000 for telephony audio. |
| Flush signal | flush_signal=True + await ws.flush() forces immediate transcription boundary. |
| Short audio detection | Set language_code explicitly for audio <3 seconds — auto-detection needs more signal. |
Full Docs
Fetch streaming protocol, batch API SDK examples, and codec details from:
