# Source: https://docs.pipecat.ai/deployment/pipecat-cloud/guides/smart-turn.md

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pipecat.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Smart Turn Detection

> Advanced conversational turn detection

## Overview

Smart Turn Detection uses an advanced machine learning model to determine when a user has finished speaking and your bot should respond. Unlike basic Voice Activity Detection (VAD) which only detects speech vs. non-speech, Smart Turn Detection recognizes natural conversational cues like intonation patterns and linguistic signals for more natural conversations.

<CardGroup cols={2}>
  <Card title="GitHub Repository" icon="github" href="https://github.com/pipecat-ai/smart-turn">
    Open source model for conversational turn detection
  </Card>

  <Card title="Model weights" icon="face-smiling-hands" href="https://huggingface.co/pipecat-ai/smart-turn-v3/tree/main">
    ONNX weights file for Smart Turn v3
  </Card>
</CardGroup>

## Key Benefits

* **Natural conversations**: More human-like turn-taking patterns
* **Free to use**: The model is fully open source
* **Scalable**: Smart Turn v3 supports fast CPU inference directly inside your Pipecat Cloud instance

## Quick Start

To enable Smart Turn Detection in your Pipecat Cloud bot, configure a `TurnAnalyzerUserTurnStopStrategy` with `LocalSmartTurnAnalyzerV3` in your context aggregator.

The model weights are bundled with Pipecat, so there's no need to download them separately.

```python  theme={null}
from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.processors.aggregators.llm_response_universal import (
    LLMContextAggregatorPair,
    LLMUserAggregatorParams,
)
from pipecat.transports.daily.transport import DailyParams, DailyTransport
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies

async def main(room_url: str, token: str):
    transport = DailyTransport(
        room_url,
        token,
        "Voice AI Bot",
        DailyParams(
            audio_in_enabled=True,
            audio_out_enabled=True,
        ),
    )

    # Configure Smart Turn Detection via user turn strategies
    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
        context,
        user_params=LLMUserAggregatorParams(
            user_turn_strategies=UserTurnStrategies(
                stop=[TurnAnalyzerUserTurnStopStrategy(
                    turn_analyzer=LocalSmartTurnAnalyzerV3()
                )]
            ),
            vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
        ),
    )

    # Continue with your pipeline setup...
```

<Tip>
  Smart Turn Detection requires VAD to be enabled with `stop_secs=0.2`. This
  value mimics the training data and allows Smart Turn to dynamically adjust
  timing based on the model's predictions.
</Tip>

## How It Works

1. **Audio Analysis**: The system continuously analyzes incoming audio for speech patterns
2. **VAD Processing**: Voice Activity Detection segments audio into speech and silence
3. **Turn Classification**: When VAD detects a pause, the ML model analyzes the speech segment for natural completion cues
4. **Smart Response**: The model determines if the turn is complete or if the user is likely to continue speaking

## Training Data Collection

The smart-turn model is trained on real conversational data collected through these applications. Help us improve the model by contributing your own data or classifying existing data:

<CardGroup cols={2}>
  <Card title="Data Collector" icon="microphone" href="https://turn-training.pipecat.ai/">
    Contribute conversational data to improve the model
  </Card>

  <Card title="Data Classifier" icon="check-circle" href="https://smart-turn-dataset.pipecat.ai/">
    Help classify turn completion patterns in conversations
  </Card>
</CardGroup>

## More information

For more details on Smart Turn, see the following links:

<CardGroup cols={2}>
  <Card title="Smart Turn Overview" href="../../../server/utilities/smart-turn/smart-turn-overview">
    More details about the Pipecat Smart Turn integration
  </Card>
</CardGroup>