Multi-Voice Dialogue

Generate conversations with multiple distinct voices

Create natural-sounding dialogues and conversations with up to 10 different voices. Perfect for audiobooks, podcasts, training materials, and interactive content.

Quick Start

from elevenlabs import ElevenLabs
from elevenlabs.types import DialogueInput

client = ElevenLabs(api_key="YOUR_API_KEY")

# Create a simple dialogue
dialogue = [
    DialogueInput(
        text="Hello! How can I help you today?",
        voice_id="21m00Tcm4TlvDq8ikWAM"  # Rachel
    ),
    DialogueInput(
        text="I'd like to know more about your services.",
        voice_id="AZnzlk1XvdvUeBnXmlld"  # Domi
    )
]

audio = client.text_to_dialogue.convert(inputs=dialogue)

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

Features

Multiple Voices

Use up to 10 different voices in a single dialogue

Natural Flow

Seamless transitions between speakers

Timestamps

Get timing information for each voice segment

High Quality

Professional audio output with natural pacing

Creating Dialogues

Basic Conversation

from elevenlabs import ElevenLabs
from elevenlabs.types import DialogueInput

client = ElevenLabs(api_key="YOUR_API_KEY")

# Define the dialogue
dialogue = [
    DialogueInput(
        text="Welcome to our store! How may I assist you?",
        voice_id="voice_id_1"  # Store employee
    ),
    DialogueInput(
        text="Hi! I'm looking for a birthday gift.",
        voice_id="voice_id_2"  # Customer
    ),
    DialogueInput(
        text="Wonderful! What does the person enjoy?",
        voice_id="voice_id_1"  # Store employee
    ),
    DialogueInput(
        text="They love reading mystery novels.",
        voice_id="voice_id_2"  # Customer
    )
]

# Generate the dialogue
audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    model_id="eleven_multilingual_v2"
)

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

Audiobook with Character Voices

# Audiobook excerpt with narrator and character voices
audiobook_dialogue = [
    DialogueInput(
        text="The detective entered the dimly lit room,",
        voice_id="narrator_voice_id"
    ),
    DialogueInput(
        text="Someone's been here recently,",
        voice_id="detective_voice_id"
    ),
    DialogueInput(
        text="she said, examining the scattered papers.",
        voice_id="narrator_voice_id"
    ),
    DialogueInput(
        text="What are you doing here?",
        voice_id="suspect_voice_id"
    ),
    DialogueInput(
        text="a voice called from the doorway.",
        voice_id="narrator_voice_id"
    )
]

audio = client.text_to_dialogue.convert(
    inputs=audiobook_dialogue,
    model_id="eleven_v3"
)

Podcast with Multiple Hosts

# Podcast episode intro
podcast_intro = [
    DialogueInput(
        text="Welcome back to Tech Talk! I'm Sarah.",
        voice_id="host_1_voice_id"
    ),
    DialogueInput(
        text="And I'm Mike. Today we're discussing AI.",
        voice_id="host_2_voice_id"
    ),
    DialogueInput(
        text="That's right! We have an exciting topic.",
        voice_id="host_1_voice_id"
    ),
    DialogueInput(
        text="Let's dive right in!",
        voice_id="host_2_voice_id"
    )
]

audio = client.text_to_dialogue.convert(
    inputs=podcast_intro,
    model_id="eleven_turbo_v2_5"  # Fast generation
)

Advanced Features

Dialogue with Timestamps

Get timing information for each voice segment:

# Generate dialogue with timestamp data
result = client.text_to_dialogue.convert_with_timestamps(
    inputs=dialogue,
    model_id="eleven_multilingual_v2"
)

# Access audio data
audio_data = result.audio

# Access timestamp information
for segment in result.voice_segments:
    print(f"Voice {segment.voice_id}:")
    print(f"  Start: {segment.start_time}s")
    print(f"  End: {segment.end_time}s")
    print(f"  Text: {segment.text}")

Streaming Dialogue

Stream dialogue generation in real-time:

from elevenlabs import stream

# Stream the dialogue
audio_stream = client.text_to_dialogue.stream(
    inputs=dialogue,
    model_id="eleven_turbo_v2_5"
)

# Play as it generates
stream(audio_stream)

# Or process chunks manually
for chunk in audio_stream:
    # Process each audio chunk
    pass

Customization

Model Selection

# Use Eleven v3 for dramatic performances
audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    model_id="eleven_v3"
)

# Use Turbo for faster generation
audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    model_id="eleven_turbo_v2_5"
)

# Use Multilingual v2 for best stability
audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    model_id="eleven_multilingual_v2"
)

Language Support

# Specify language for better pronunciation
audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    language_code="es",  # Spanish
    model_id="eleven_multilingual_v2"
)

Custom Voice Settings

from elevenlabs.types import ModelSettingsResponseModel

# Apply custom settings
settings = ModelSettingsResponseModel(
    stability=0.7,
    similarity_boost=0.8
)

audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    settings=settings,
    model_id="eleven_multilingual_v2"
)

Pronunciation Dictionaries

from elevenlabs.types import PronunciationDictionaryVersionLocator

# Use pronunciation dictionary for technical terms
dictionaries = [
    PronunciationDictionaryVersionLocator(
        pronunciation_dictionary_id="dict_id",
        version_id="version_id"
    )
]

audio = client.text_to_dialogue.convert(
    inputs=dialogue,
    pronunciation_dictionary_locators=dictionaries
)

Async Usage

from elevenlabs import AsyncElevenLabs
import asyncio

async def generate_dialogue():
    client = AsyncElevenLabs(api_key="YOUR_API_KEY")
    
    dialogue = [
        {"text": "Hello there!", "voice_id": "voice_1"},
        {"text": "Hi! Nice to meet you.", "voice_id": "voice_2"}
    ]
    
    audio = await client.text_to_dialogue.convert(inputs=dialogue)
    
    chunks = []
    async for chunk in audio:
        chunks.append(chunk)
    
    return b"".join(chunks)

audio_data = asyncio.run(generate_dialogue())

Use Cases

Educational Content

# Create interactive learning content
educational_dialogue = [
    DialogueInput(
        text="Today we'll learn about photosynthesis.",
        voice_id="teacher_voice"
    ),
    DialogueInput(
        text="What is photosynthesis?",
        voice_id="student_voice"
    ),
    DialogueInput(
        text="Great question! It's how plants make food.",
        voice_id="teacher_voice"
    )
]

Customer Service Training

# Training scenarios
training_scenario = [
    DialogueInput(
        text="Thank you for calling. How can I help you?",
        voice_id="agent_voice"
    ),
    DialogueInput(
        text="I have a problem with my recent order.",
        voice_id="customer_voice"
    ),
    DialogueInput(
        text="I'm sorry to hear that. Let me help you.",
        voice_id="agent_voice"
    )
]

Interactive Stories

# Choose-your-own-adventure style content
story_dialogue = [
    DialogueInput(
        text="You find yourself at a crossroads.",
        voice_id="narrator_voice"
    ),
    DialogueInput(
        text="Which path will you take?",
        voice_id="narrator_voice"
    )
]

Best Practices

Voice Selection

• Choose distinct voices for each character
• Match voice characteristics to character traits
• Use consistent voices throughout the dialogue
• Test voice combinations before production

Script Writing

• Write natural, conversational text
• Include appropriate pauses with punctuation
• Keep individual segments concise
• Vary sentence structure for natural flow

Performance Optimization

• Use Turbo models for faster generation
• Consider streaming for long dialogues
• Batch process multiple dialogues with async
• Cache frequently used voice combinations

Limitations

• Maximum of 10 unique voice IDs per dialogue
• Total text length may be limited by your subscription tier
• Generation time increases with dialogue length and number of voices

Related Features

• Text to Speech - Single voice generation
• Voice Cloning - Create custom voices
• Voices - Browse available voices