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Model selection

For the complete documentation index, see llms.txt

The speech_model connection parameter lets you specify which model to use for streaming transcription.

You must include the speech_model parameter in every streaming transcription request. There is no default model. If you omit speech_model, the request will fail.

We recommend Universal-3 Pro Streaming as your primary model for streaming transcription. It provides the highest accuracy with sub-300ms latency, native multilingual code switching, and advanced prompting support — ideal for voice agents and real-time applications.

Available models

Name	Parameter	Description	Best for
Universal-3 Pro Streaming	"speech_model": "u3-rt-pro"	The most accurate model with the fastest word emissions for voice agents that demand the highest quality. Best-in-class accuracy with advanced prompting capabilities. Supports EN, ES, DE, FR, PT, IT.	Real-time voice agents needing premium accuracy, elite entity accuracy, IVR replacement, agent assist, multilingual code-switching
Universal-Streaming English	"speech_model": "universal-streaming-english"	An English transcription model offering a good balance of speed and cost-effectiveness.	Cost-effective English real-time transcription, English-only real-time apps
Universal-Streaming Multilingual	"speech_model": "universal-streaming-multilingual"	A multilingual transcription model offering a good balance of speed and cost-effectiveness. Supports EN, ES, DE, FR, PT, IT.	Cost-effective multilingual streaming across EN/ES/DE/FR/PT/IT
Whisper Streaming	"speech_model": "whisper-rt"	An open-source Whisper model enhanced with AssemblyAI's reliable infrastructure and unlimited scale. Supports 99+ languages at an accessible price point.	Language coverage beyond 6 languages, open-source model preference, cost-sensitive multilingual transcription

Choosing a model

Feature	Universal-3 Pro Streaming	Universal-Streaming English	Universal-Streaming Multilingual	Whisper Streaming
Latency	Fast	Fastest	Fast	Moderate
Partial transcripts	Yes	Yes	Yes	Yes
Multilingual	Native Code Switching	No	Per Turn	99+ languages (auto-detected)
Entity accuracy	Best	Okay	Okay	Okay
Disfluencies & filler words	Yes	No	No	No
Language detection	Yes	No	Yes	Yes (with confidence scores)
Non-speech tags	No	No	No	Yes ([Silence], [Music], etc.)
Customization	Keyterms prompting (known context) + Native prompting (unknown context)	Keyterms prompting (known context)	Keyterms prompting (known context)	No

For detailed setup and configuration of Universal-3 Pro streaming, see the Universal-3 Pro Streaming page. For prompting guidance, see the Prompting guide.

For detailed setup and configuration of Whisper streaming, see this page.

End-to-end example

You can select a model by setting the speech_model connection parameter when connecting to the streaming API:

import pyaudio
import websocket
import json
import threading
import time
from urllib.parse import urlencode

YOUR_API_KEY = "<YOUR_API_KEY>"

CONNECTION_PARAMS = {
    "sample_rate": 16000,
    "speech_model": "u3-rt-pro",  # or "universal-streaming-english", "universal-streaming-multilingual", "whisper-rt"
    "min_turn_silence": 100,
    "max_turn_silence": 1000,
    # "format_turns": True,  # Whether to return formatted final transcripts (not applicable to u3-rt-pro)
}
API_ENDPOINT_BASE_URL = "wss://streaming.assemblyai.com/v3/ws"
API_ENDPOINT = f"{API_ENDPOINT_BASE_URL}?{urlencode(CONNECTION_PARAMS)}"

FRAMES_PER_BUFFER = 800
SAMPLE_RATE = CONNECTION_PARAMS["sample_rate"]
CHANNELS = 1
FORMAT = pyaudio.paInt16

audio = None
stream = None
ws_app = None
audio_thread = None
stop_event = threading.Event()

def on_open(ws):
    print("WebSocket connection opened.")
    def stream_audio():
        global stream
        while not stop_event.is_set():
            try:
                audio_data = stream.read(FRAMES_PER_BUFFER, exception_on_overflow=False)
                ws.send(audio_data, websocket.ABNF.OPCODE_BINARY)
            except Exception as e:
                print(f"Error streaming audio: {e}")
                break

    global audio_thread
    audio_thread = threading.Thread(target=stream_audio)
    audio_thread.daemon = True
    audio_thread.start()

def on_message(ws, message):
    try:
        data = json.loads(message)
        msg_type = data.get("type")

        if msg_type == "Begin":
            print(f"Session began: ID={data.get('id')}")
        elif msg_type == "Turn":
            transcript = data.get("transcript", "")
            end_of_turn = data.get("end_of_turn", False)
            if end_of_turn:
                print(f"\r{' ' * 80}\r{transcript}")
            else:
                print(f"\r{transcript}", end="")
        elif msg_type == "Termination":
            print(f"\nSession terminated: {data.get('audio_duration_seconds', 0)}s of audio")
    except Exception as e:
        print(f"Error handling message: {e}")

def on_error(ws, error):
    print(f"\nWebSocket Error: {error}")
    stop_event.set()

def on_close(ws, close_status_code, close_msg):
    print(f"\nWebSocket Disconnected: Status={close_status_code}")
    global stream, audio
    stop_event.set()
    if stream:
        if stream.is_active():
            stream.stop_stream()
        stream.close()
    if audio:
        audio.terminate()

def run():
    global audio, stream, ws_app

    audio = pyaudio.PyAudio()
    stream = audio.open(
        input=True,
        frames_per_buffer=FRAMES_PER_BUFFER,
        channels=CHANNELS,
        format=FORMAT,
        rate=SAMPLE_RATE,
    )
    print("Speak into your microphone. Press Ctrl+C to stop.")

    ws_app = websocket.WebSocketApp(
        API_ENDPOINT,
        header={"Authorization": YOUR_API_KEY},
        on_open=on_open,
        on_message=on_message,
        on_error=on_error,
        on_close=on_close,
    )

    ws_thread = threading.Thread(target=ws_app.run_forever)
    ws_thread.daemon = True
    ws_thread.start()

    try:
        while ws_thread.is_alive():
            time.sleep(0.1)
    except KeyboardInterrupt:
        print("\nStopping...")
        stop_event.set()
        if ws_app and ws_app.sock and ws_app.sock.connected:
            ws_app.send(json.dumps({"type": "Terminate"}))
            time.sleep(2)
        if ws_app:
            ws_app.close()
        ws_thread.join(timeout=2.0)

if __name__ == "__main__":
    run()

import logging
from typing import Type

import assemblyai as aai
from assemblyai.streaming.v3 import (
    BeginEvent,
    StreamingClient,
    StreamingClientOptions,
    StreamingError,
    StreamingEvents,
    StreamingParameters,
    TurnEvent,
    TerminationEvent,
)

api_key = "<YOUR_API_KEY>"

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def on_begin(self: Type[StreamingClient], event: BeginEvent):
    print(f"Session started: {event.id}")

def on_turn(self: Type[StreamingClient], event: TurnEvent):
    print(f"{event.transcript} ({event.end_of_turn})")

def on_terminated(self: Type[StreamingClient], event: TerminationEvent):
    print(
        f"Session terminated: {event.audio_duration_seconds} seconds of audio processed"
    )

def on_error(self: Type[StreamingClient], error: StreamingError):
    print(f"Error occurred: {error}")

def main():
    client = StreamingClient(
        StreamingClientOptions(
            api_key=api_key,
            api_host="streaming.assemblyai.com",
        )
    )

    client.on(StreamingEvents.Begin, on_begin)
    client.on(StreamingEvents.Turn, on_turn)
    client.on(StreamingEvents.Termination, on_terminated)
    client.on(StreamingEvents.Error, on_error)

    client.connect(
        StreamingParameters(
            sample_rate=16000,
            speech_model="u3-rt-pro",  # or "universal-streaming-english", "universal-streaming-multilingual", "whisper-rt"
            min_turn_silence=100,
            max_turn_silence=1000,
            # format_turns=True,  # Whether to return formatted final transcripts (not applicable to u3-rt-pro)
        )
    )

    try:
        client.stream(
            aai.extras.MicrophoneStream(sample_rate=16000)
        )
    finally:
        client.disconnect(terminate=True)

if __name__ == "__main__":
    main()

const WebSocket = require("ws");
const mic = require("mic");
const querystring = require("querystring");

const YOUR_API_KEY = "<YOUR_API_KEY>";
const CONNECTION_PARAMS = {
  sample_rate: 16000,
  speech_model: "u3-rt-pro", // or "universal-streaming-english", "universal-streaming-multilingual", "whisper-rt"
  min_turn_silence: 100,
  max_turn_silence: 1000,
  // format_turns: true, // Whether to return formatted final transcripts (not applicable to u3-rt-pro)
};
const API_ENDPOINT_BASE_URL = "wss://streaming.assemblyai.com/v3/ws";
const API_ENDPOINT = `${API_ENDPOINT_BASE_URL}?${querystring.stringify(CONNECTION_PARAMS)}`;

const SAMPLE_RATE = CONNECTION_PARAMS.sample_rate;

let micInstance = null;
let ws = null;

function run() {
  console.log("Starting AssemblyAI streaming transcription...");

  ws = new WebSocket(API_ENDPOINT, {
    headers: { Authorization: YOUR_API_KEY },
  });

  ws.on("open", () => {
    console.log("WebSocket connection opened.");

    micInstance = mic({
      rate: String(SAMPLE_RATE),
      channels: "1",
      bitwidth: "16",
      encoding: "signed-integer",
      endian: "little",
    });

    const micInputStream = micInstance.getAudioStream();
    micInputStream.on("data", (data) => {
      if (ws.readyState === WebSocket.OPEN) {
        ws.send(data);
      }
    });

    micInstance.start();
    console.log("Speak into your microphone. Press Ctrl+C to stop.");
  });

  ws.on("message", (data) => {
    try {
      const msg = JSON.parse(data);
      if (msg.type === "Begin") {
        console.log(`Session began: ID=${msg.id}`);
      } else if (msg.type === "Turn") {
        const transcript = msg.transcript || "";
        if (msg.end_of_turn) {
          process.stdout.write("\r" + " ".repeat(80) + "\r");
          console.log(transcript);
        } else {
          process.stdout.write(`\r${transcript}`);
        }
      } else if (msg.type === "Termination") {
        console.log(
          `\nSession terminated: ${msg.audio_duration_seconds}s of audio`
        );
      }
    } catch (e) {
      console.error("Error parsing message:", e);
    }
  });

  ws.on("error", (error) => {
    console.error("WebSocket error:", error);
  });

  ws.on("close", (code, reason) => {
    console.log(`WebSocket closed: ${code}`);
    if (micInstance) micInstance.stop();
  });

  process.on("SIGINT", () => {
    console.log("\nStopping...");
    if (micInstance) micInstance.stop();
    if (ws && ws.readyState === WebSocket.OPEN) {
      ws.send(JSON.stringify({ type: "Terminate" }));
      setTimeout(() => ws.close(), 2000);
    }
  });
}

run();

import { Readable } from "stream";
import { AssemblyAI } from "assemblyai";
import recorder from "node-record-lpcm16";

const run = async () => {
  const client = new AssemblyAI({
    apiKey: "<YOUR_API_KEY>",
  });

  const transcriber = client.streaming.transcriber({
    sampleRate: 16_000,
    speechModel: "u3-rt-pro", // or "universal-streaming-english", "universal-streaming-multilingual", "whisper-rt"
    minTurnSilence: 100,
    maxTurnSilence: 1000,
    // formatTurns: true, // Whether to return formatted final transcripts (not applicable to u3-rt-pro)
  });

  transcriber.on("open", ({ id }) => {
    console.log(`Session opened with ID: ${id}`);
  });

  transcriber.on("error", (error) => {
    console.error("Error:", error);
  });

  transcriber.on("close", (code, reason) =>
    console.log("Session closed:", code, reason)
  );

  transcriber.on("turn", (turn) => {
    if (!turn.transcript) {
      return;
    }

    console.log("Turn:", turn.transcript);
  });

  try {
    console.log("Connecting to streaming transcript service");
    await transcriber.connect();

    console.log("Starting recording");
    const recording = recorder.record({
      channels: 1,
      sampleRate: 16_000,
      audioType: "wav",
    });

    Readable.toWeb(recording.stream()).pipeTo(transcriber.stream());

    process.on("SIGINT", async function () {
      console.log();
      console.log("Stopping recording");
      recording.stop();

      console.log("Closing streaming transcript connection");
      await transcriber.close();

      process.exit();
    });
  } catch (error) {
    console.error(error);
  }
};

run();