---
title: "Noise Filtering | Micdrop"
description: "User noise filtering automatically filters out meaningless sounds like \"uh\", \"hmm\", \"ahem\" that don't carry conversational meaning, improving the quality of…"
url: "https://micdrop.dev/docs/server/noise-filtering"
---

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[Micdrop](/) › [Documentation](/docs/getting-started) › [Server (Node.js)](/docs/server)

# Noise Filtering

User noise filtering automatically filters out meaningless sounds like “uh”, “hmm”, “ahem” that don’t carry conversational meaning, improving the quality of conversation flow.

## Usage

```
const agent = new OpenaiAgent({  apiKey: process.env.OPENAI_API_KEY || '',  systemPrompt: 'You are a helpful assistant',  autoIgnoreUserNoise: true, // Ignore filler sounds  // or provide custom prompt:  // autoIgnoreUserNoise: 'Last user message is just an interjection',})
```

## Configuration Options

Option

Type

Description

`autoIgnoreUserNoise`

`boolean | string`

Enable filtering or provide custom prompt

*   **`true`**: Uses the default noise detection logic
*   **`string`**: Provides a custom prompt for the AI to use when determining if a message is just noise

## How it Works

A specific tool is added to the query, that will be called when the agent detects that the user message is just noise. When a noise is detected, the agent automatically emits an `CancelLastUserMessage` to removed and ignore the last user message.

## Common Filtered Sounds

The system typically filters out:

*   Filler words: “uh”, “um”, “er”
*   Interjections: “hmm”, “ahem”, “oh”
*   Breathing sounds and background noise
*   Partial words or unclear utterances

## Example Scenarios

**Without User Noise Filtering:**

*   User: “Um…”
*   Agent: “I’m sorry, I didn’t understand. Could you please repeat that?”
*   User: “I want to book a flight”

**With User Noise Filtering:**

*   User: “Um…”
*   _Agent ignores the noise_
*   User: “I want to book a flight”
*   Agent: “I’d be happy to help you book a flight. Where would you like to go?”

## Best Practices

*   Consider the quality of your speech-to-text service when configuring
*   Test with various noise patterns to ensure legitimate short responses aren’t filtered
*   Balance filtering with responsiveness to avoid ignoring valid but brief user input
*   Monitor conversation logs to ensure important utterances aren’t being filtered out

[Previous← Semantic Turn Detection](/docs/server/semantic-turn-detection)[NextMicdrop Protocol →](/docs/server/protocol)

On this page

*   [Usage](#usage)
*   [Configuration Options](#configuration-options)
*   [How it Works](#how-it-works)
*   [Common Filtered Sounds](#common-filtered-sounds)
*   [Example Scenarios](#example-scenarios)
*   [Best Practices](#best-practices)