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Speech to Text

Transcribe Indian-language audio, a file at a time or live as it is spoken.

Transcription comes in two modes. They share models, credentials, and pricing, and differ in when you get results.

Non-streaming

Upload a recording, get the whole transcript back in the response, with per-segment timings and confidence when you ask for them.

Best for recorded calls, voicemail, archives, and anything where you already have the whole file.

Streaming

Open a WebSocket, push audio frames as they arrive, read transcripts back as the words are still being spoken. Partial results refine into final ones on the same connection.

Best for live calls, real-time captioning, and voice agents.

Choosing between them

Non-streaming Streaming
Endpoint POST stt.navana.ai/api/transcribe wss://stt.navana.ai
Protocol Multipart upload WebSocket
Input An audio file Raw PCM16 frames, any size
Result Once, complete Continuously, refining
Billed on Seconds of audio Seconds connected
Timings and confidence Per segment, with aux Per segment, plus per-token timestamps

If you already have the whole file, use the non-streaming endpoint. It is the simpler of the two.

What comes back

Both modes return more than a string. Segments carry timings and confidence scores, and streaming adds per-token timestamps.

That supports a few things a plain transcript does not:

  • Align a transcript to playback. Click a sentence, seek the audio to it.
  • Route low-confidence spans to human review instead of accepting or rejecting whole transcripts.
  • Measure talk time and silence from segment boundaries.
  • Trigger on a phrase mid-call by watching partial results as they arrive.

Languages and models

Ten Indian languages plus a Hinglish compatibility code, each trained at 8 kHz for telephony audio. Most are bilingual with English, so code-switching mid-sentence is handled. Gujarati and Odia are monolingual, and English has a dedicated English-only model.

See Models and languages for the full list and how to choose.

Start here

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