> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/elevenlabs/elevenlabs-python/llms.txt
> Use this file to discover all available pages before exploring further.

# Sound Effects Generation

> Create realistic sound effects from text descriptions using AI

Generate professional-quality sound effects for your videos, games, podcasts, and voice-overs using the most advanced sound effects AI models.

## Quick Start

```python theme={null}
from elevenlabs import ElevenLabs

client = ElevenLabs(api_key="YOUR_API_KEY")

# Generate a sound effect
audio = client.text_to_sound_effects.convert(
    text="thunder crashing in the distance",
    duration_seconds=3.0
)

# Save to file
with open("thunder.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)
```

## Features

<CardGroup cols={2}>
  <Card title="Natural Sounds" icon="leaf">
    Generate realistic environmental sounds like rain, wind, or thunder
  </Card>

  <Card title="Seamless Looping" icon="arrows-rotate">
    Create sound effects designed to loop smoothly
  </Card>

  <Card title="Custom Duration" icon="clock">
    Specify exact duration for your sound effects
  </Card>

  <Card title="High Quality" icon="star">
    Professional-grade audio output in multiple formats
  </Card>
</CardGroup>

## Basic Usage

### Generate a Sound Effect

```python theme={null}
from elevenlabs import ElevenLabs

client = ElevenLabs(api_key="YOUR_API_KEY")

audio = client.text_to_sound_effects.convert(
    text="waves crashing on a beach",
    duration_seconds=5.0
)

with open("waves.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)
```

### Create Looping Sound Effects

```python theme={null}
# Generate a seamlessly looping sound
audio = client.text_to_sound_effects.convert(
    text="gentle rain falling",
    duration_seconds=10.0,
    loop=True  # Optimized for seamless looping
)

with open("rain_loop.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)
```

## Parameters

### Text Description

The text parameter accepts natural language descriptions of the sound you want to create:

```python theme={null}
# Environmental sounds
client.text_to_sound_effects.convert(text="wind howling through trees")

# Mechanical sounds
client.text_to_sound_effects.convert(text="old door creaking open")

# Nature sounds
client.text_to_sound_effects.convert(text="birds chirping in the morning")

# Urban sounds
client.text_to_sound_effects.convert(text="city traffic ambience")
```

### Duration Control

```python theme={null}
# Short sound effect (1 second)
audio = client.text_to_sound_effects.convert(
    text="door knock",
    duration_seconds=1.0
)

# Medium sound effect (5 seconds)
audio = client.text_to_sound_effects.convert(
    text="rain ambience",
    duration_seconds=5.0
)

# Long ambient sound (30 seconds)
audio = client.text_to_sound_effects.convert(
    text="ocean waves",
    duration_seconds=30.0
)
```

### Prompt Influence

Control how closely the generation follows your text description:

```python theme={null}
# High influence - very literal interpretation
audio = client.text_to_sound_effects.convert(
    text="glass breaking",
    prompt_influence=0.9
)

# Medium influence - balanced
audio = client.text_to_sound_effects.convert(
    text="footsteps on gravel",
    prompt_influence=0.5
)

# Low influence - more creative interpretation
audio = client.text_to_sound_effects.convert(
    text="mysterious atmosphere",
    prompt_influence=0.2
)
```

## Output Formats

```python theme={null}
# MP3 format (default)
audio = client.text_to_sound_effects.convert(
    text="thunder",
    output_format="mp3_22050_32"
)

# High-quality MP3
audio = client.text_to_sound_effects.convert(
    text="thunder",
    output_format="mp3_44100_192"  # Requires Creator tier or above
)

# PCM format for editing
audio = client.text_to_sound_effects.convert(
    text="thunder",
    output_format="pcm_44100"  # Requires Pro tier or above
)
```

## Async Usage

```python theme={null}
from elevenlabs import AsyncElevenLabs
import asyncio

async def generate_sound_effect():
    client = AsyncElevenLabs(api_key="YOUR_API_KEY")
    
    audio = await client.text_to_sound_effects.convert(
        text="explosion in the distance",
        duration_seconds=3.0
    )
    
    chunks = []
    async for chunk in audio:
        chunks.append(chunk)
    
    return b"".join(chunks)

audio_data = asyncio.run(generate_sound_effect())
```

## Batch Generation

Generate multiple sound effects efficiently:

```python theme={null}
from elevenlabs import AsyncElevenLabs
import asyncio

async def generate_multiple_effects():
    client = AsyncElevenLabs(api_key="YOUR_API_KEY")
    
    sound_descriptions = [
        "thunder",
        "rain",
        "wind",
        "fire crackling"
    ]
    
    tasks = [
        client.text_to_sound_effects.convert(
            text=desc,
            duration_seconds=5.0
        )
        for desc in sound_descriptions
    ]
    
    results = await asyncio.gather(*tasks)
    
    # Save each sound effect
    for i, (desc, audio) in enumerate(zip(sound_descriptions, results)):
        chunks = []
        async for chunk in audio:
            chunks.append(chunk)
        
        with open(f"{desc.replace(' ', '_')}.mp3", "wb") as f:
            f.write(b"".join(chunks))

asyncio.run(generate_multiple_effects())
```

## Use Cases

### Video Production

```python theme={null}
# Generate ambient background sounds
ambient = client.text_to_sound_effects.convert(
    text="busy coffee shop atmosphere",
    duration_seconds=30.0,
    loop=True
)

# Generate specific action sounds
action = client.text_to_sound_effects.convert(
    text="car door slam",
    duration_seconds=2.0
)
```

### Game Development

```python theme={null}
# Background ambience
forest_ambience = client.text_to_sound_effects.convert(
    text="forest with birds and insects",
    duration_seconds=60.0,
    loop=True
)

# Interactive sounds
footsteps = client.text_to_sound_effects.convert(
    text="footsteps on wooden floor",
    duration_seconds=1.0
)
```

### Podcast Production

```python theme={null}
# Intro/outro sounds
intro = client.text_to_sound_effects.convert(
    text="upbeat notification sound",
    duration_seconds=2.0
)

# Transition effects
transition = client.text_to_sound_effects.convert(
    text="swoosh transition",
    duration_seconds=1.0
)
```

## Best Practices

<AccordionGroup>
  <Accordion title="Writing Effective Descriptions">
    * Be specific about the sound you want
    * Include details about intensity, distance, and environment
    * Use descriptive adjectives ("loud", "gentle", "distant")
    * Mention specific objects or actions ("glass shattering", "metal clanging")
  </Accordion>

  <Accordion title="Duration Guidelines">
    * Short effects (0.5-2s): Impacts, hits, notifications
    * Medium effects (3-10s): Transitions, specific actions
    * Long effects (15-60s): Ambient backgrounds, atmospheres
    * Use looping for continuous backgrounds
  </Accordion>

  <Accordion title="Format Selection">
    * MP3 22050Hz: Good for web, small file size
    * MP3 44100Hz: Better quality, larger files
    * PCM: Best for editing and post-processing
    * WAV: Lossless quality for professional use
  </Accordion>
</AccordionGroup>

## Limitations

<Warning>
  * Maximum duration may vary based on your subscription tier
  * High-quality formats (192kbps MP3, PCM, WAV) require higher subscription tiers
  * Generation time increases with duration
</Warning>

## Related Features

* [Music Generation](/advanced/music-generation) - Create background music
* [Text to Speech](/text-to-speech) - Generate voice narration
* [Dialogue](/advanced/dialogue) - Multi-voice conversations