Streaming Transcription API

Stream audio to Convai’s ASR engine using WebSockets and receive real-time transcriptions. Designed for low-latency, intelligent voice experiences with your AI characters.

This API is available only on the Enterprise Plan.

This API is still in development and is currently a beta feature.

All the relevant API details needed to stream real-time audio input and receive text transcription from Convai’s ASR (Automatic Speech Recognition) engine.

Access this endpoint to enable live speech recognition within Convai-based applications, voice-enabled AI characters. Once connected, the WebSocket channel streams audio in and transcriptions out, enabling responsive, conversational experiences.

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Overview

Base URL:

https://transcribe.convai.com

WebSocket Endpoint:

wss://transcribe.convai.com/stream

Protocol: Bidirectional — stream 16-bit PCM audio in, receive transcript events out.

Supported Languages: English

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Authentication

Provide your Convai API key during the initial WebSocket handshake.

Headers

Name	Type	Description
CONVAI-API-KEY	String	Your unique API key, found in your Convai account.

Alternative (Query Parameter)

If header authentication is not possible:

wss://transcribe.convai.com/stream?convai-api-key=<your-api-key>

If your API key is missing or invalid, the connection will close immediately with an error event.

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Connect Session

wss://transcribe.convai.com/stream

Description

Establishes a live WebSocket connection with Convai’s transcription service. Once the session is active, you can send binary audio frames and receive incremental (transcript.partial) and finalized (transcript.final) transcripts.

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Session Start Example

{
  "type": "session.started",
  "data": {
    "session_id": "f1428g2-335...",
    "expires_at": "2025-10-13T12:00:00+00:00"
  }
}

Session Close Example

{
  "type": "session.closed",
  "data": {}
}

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Response (Server Event) Body

Although WebSockets are used (not traditional JSON POSTs), message payloads follow this structure:

Name	Type	Description
type	String	Message type, such as finalize, stop, or close.
data	Object	Optional data fields depending on the message type.

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WebSocket Event Reference

Event Type	Description	Example Payload
session.started	Sent by the server once a session is successfully initialized.	{"type": "session.started", "data": {"session_id": "...", "expires_at": "..."}}
session.closed	Indicates that the session has ended gracefully.	{"type": "session.closed", "data": {}}
transcript.partial	Partial transcription updates (non-final).	{"type": "transcript.partial", "data": {"sequence_id": 1, "text": "hel", "is_final": false}}
transcript.final	Finalized transcription with or without formatting.	{"type": "transcript.final", "data": {"sequence_id": 1, "text": "Hello world.", "is_final": true, "is_formatted": true}}
error	Returned when invalid data, API key, or connection issues occur.	{"type": "error", "data": {"message": "Invalid API key."}}

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Common Data Fields

Field	Type	Description
sequence_id	Integer	Counter for ordering transcript messages.
text	String	Transcript string received so far.
is_final	Boolean	True when the transcription for the current utterance is finalized.
is_formatted	Boolean	True when punctuation and casing have been applied.
message_type	String	Metadata tag, e.g., Turn or FinalTranscript.
language_code	String / null	Detected language. Experimental Feature, can be null.

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Streaming Audio Requirements

Parameter	Specification
Encoding	PCM 16-bit, little-endian
Channels	Mono
Sample Rate	16 kHz
Recommended Frame Size	50–150 ms
Max Frame Size	~8 MiB

Send audio data as binary WebSocket messages.

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Control Messages

Send text-based JSON messages to manage the stream:

Command	Example	Description
Finalize	{"type": "finalize"}	Triggers the server to emit a final transcript.
Close	{"type": "close"}	Gracefully closes the WebSocket session.
Stop	{"type": "stop"}	Equivalent to close, may retain session context.

Control messages must always be sent as UTF-8 encoded text.

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Error Handling

Errors are reported as structured JSON objects.

Example Error Message

{
  "type": "error",
  "data": {
    "message": "Invalid API key or user not found."
  }
}

---

Status Codes

Code	Description
200	OK — Request/connection succeeded.
400	Bad Request — Malformed or invalid payload.
401	Unauthorized — Invalid or missing API key.
403	Forbidden — Plan not authorized for API access.
500	Internal Server Error.

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Troubleshooting

Issue	Possible Cause	Resolution
401 Unauthorized	Invalid or missing API key.	Verify your CONVAI-API-KEY header or query parameter.
No transcription received	Incorrect audio format.	Ensure PCM 16-bit, mono, 16 kHz encoding.
Frequent disconnects	Idle socket or malformed data.	Keep streaming frames; implement reconnection logic.
Punctuation missing	Unformatted transcript.	Wait for second transcript.final with "is_formatted": true.

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Example Progression (Single Utterance)

"welcome"
"welcome to the"
"welcome to the museum"   <-- transcript.final
"Welcome to the museum."  <-- transcript.final (formatted)

---

Currently, only English is supported.

Formatted transcripts (punctuation/case) are optional and may appear later.

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Example (End-to-End Streaming Client)

Below are sample implementations and commands demonstrating how to connect to the Streaming Transcription API and perform real time transcription.

End to End Streaming Client - Python

This example creates a real time transcription client using Python, WebSockets, and sounddevice for live microphone input.

Requirements:

• Python 3.8+
• pip install websockets sounddevice

File: convai_stt_stream.py

Python

# End-to-End Streaming Client
# Equivalent clients can be created for other languages.

# Requires: pip install websockets sounddevice
# Run as: python convai_stt_stream.py

import asyncio
import json
import os
import signal
import sys

import sounddevice as sd
import websockets

API_KEY = os.getenv("CONVAI_API_KEY", "REPLACE_WITH_YOUR_KEY")
WS_URL = "wss://transcribe.convai.com/stream"

SAMPLE_RATE = 16000
CHANNELS = 1
DTYPE = "int16"          # 16-bit little-endian PCM
CHUNK_MS = 100           # 50–150 ms recommended
BLOCKSIZE = int(SAMPLE_RATE * CHUNK_MS / 1000)  # frames per chunk

shutdown = asyncio.Event()

def install_signal_handlers():
    def _handler(*_):
        shutdown.set()
    for s in (signal.SIGINT, signal.SIGTERM):
        try:
            signal.signal(s, _handler)
        except Exception:
            pass

async def sender(ws, audio_q: asyncio.Queue):
    try:
        while not shutdown.is_set():
            try:
                chunk = await asyncio.wait_for(audio_q.get(), timeout=0.25)
            except asyncio.TimeoutError:
                continue
            await ws.send(chunk)
    except asyncio.CancelledError:
        pass

async def receiver(ws):
    try:
        async for msg in ws:
            print(msg)
    except asyncio.CancelledError:
        pass
    except websockets.ConnectionClosed:
        pass

async def main():
    if not API_KEY or API_KEY.startswith("REPLACE_"):
        print("Set CONVAI_API_KEY environment variable or update API_KEY.", file=sys.stderr)
        return 1

    loop = asyncio.get_running_loop()
    audio_q: asyncio.Queue[bytes] = asyncio.Queue(maxsize=64)

    # Create audio callback
    def make_callback(loop_):
        def _cb(indata, frames, time_info, status):
            if status:
                print(status, file=sys.stderr)
            try:
                loop_.call_soon_threadsafe(audio_q.put_nowait, bytes(indata))
            except Exception:
                pass
        return _cb

    cb = make_callback(loop)

    # Open microphone stream
    with sd.RawInputStream(
        samplerate=SAMPLE_RATE,
        channels=CHANNELS,
        dtype=DTYPE,
        blocksize=BLOCKSIZE,
        callback=cb,
    ):
        # Connect with API key as header
        async with websockets.connect(
            WS_URL,
            additional_headers={"CONVAI-API-KEY": API_KEY},
            max_size=8 * 1024 * 1024,
        ) as ws:
            # Read initial session.started if available
            try:
                msg = await asyncio.wait_for(ws.recv(), timeout=2.0)
                print(msg)
            except asyncio.TimeoutError:
                pass

            send_task = asyncio.create_task(sender(ws, audio_q))
            recv_task = asyncio.create_task(receiver(ws))

            # Wait for Ctrl+C
            await shutdown.wait()

            # Finalize current utterance and drain responses
            try:
                await ws.send(json.dumps({"type": "finalize"}))
                try:
                    while True:
                        m = await asyncio.wait_for(ws.recv(), timeout=1.0)
                        print(m)
                except asyncio.TimeoutError:
                    pass
            except Exception:
                pass

            # Close session politely
            try:
                await ws.send(json.dumps({"type": "close"}))
            except Exception:
                pass

            # Cancel background tasks cleanly
            for t in (send_task, recv_task):
                t.cancel()
            for t in (send_task, recv_task):
                try:
                    await t
                except asyncio.CancelledError:
                    pass

    return 0

if __name__ == "__main__":
    install_signal_handlers()
    try:
        rc = asyncio.run(main())
    except KeyboardInterrupt:
        rc = 0
    sys.exit(rc)

Running Steps

# 1. Install dependencies
pip install websockets sounddevice

# 2. Set your Convai API key
export CONVAI_API_KEY=<your-api-key>
# Windows PowerShell
# $Env:CONVAI_API_KEY = "<your-api-key>"

# 3. Run the streaming client
python convai_stt_stream.py

Output Example

{"type": "session.started", "data": {"session_id": "f1a2...", "expires_at": "..."}}
{"type": "transcript.partial", "data": {"text": "hello "}}
{"type": "transcript.final", "data": {"text": "Hello world.", "is_formatted": true}}
{"type": "session.closed", "data": {}}

cURL - Quick Connectivity Check

curl is not intended for WebSocket streaming. Use it to verify that the HTTPS endpoint is reachable and your key is accepted.

# Expect HTTP 200 and a short ok payload
curl -i https://transcribe.convai.com/ \
  -H "CONVAI-API-KEY: <your-api-key>"

Expected response:

{"status": "ok"}

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Conclusion

The Streaming Transcription API delivers real-time, low-latency speech recognition through WebSockets, enabling fluid and natural AI interactions. By integrating this API, you can power responsive voice-based experiences within games, assistants, or immersive Convai-enabled environments.