Piper

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Overview

PiperTTSService converts text to speech using the Piper TTS server. This service provides integration with a locally-running Piper TTS service, offering self-hosted speech synthesis capabilities.

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Installation

To use PiperTTSService, no additional dependencies in Pipecat are required.

You’ll also need to set up a running Piper TTS server following the Piper HTTP server documentation.

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Configuration

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Constructor Parameters

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Input

The service accepts text input through its TTS pipeline.

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Output Frames

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TTSStartedFrame

Signals the start of audio generation.

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TTSAudioRawFrame

Contains generated audio data:

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TTSStoppedFrame

Signals the completion of audio generation.

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ErrorFrame

Signals that an error occurred during audio generation:

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Methods

See the TTS base class methods for additional functionality.

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Usage Example

import aiohttp
from pipecat.services.piper import PiperTTSService

# Create aiohttp session
session = aiohttp.ClientSession()

# Configure service
tts = PiperTTSService(
    base_url="http://localhost:5000/api/tts",
    aiohttp_session=session,
    sample_rate=22050  # Optional: specify if you know the model's sample rate
)

# Use in pipeline
pipeline = Pipeline([
    ...,
    llm,
    tts,
    transport.output(),
])

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Frame Flow

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Metrics Support

The service supports metrics collection:

• Time to First Byte (TTFB)
• TTS usage metrics
• Processing duration

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Audio Processing

• Streams audio in 1KB chunks
• Automatically handles WAV headers in the response
• Outputs mono audio
• Supports the sample rate specified by your Piper voice model

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Notes

• Requires a running Piper TTS server
• Self-hosted solution with no external API dependencies
• Streams audio in chunks for efficient processing
• Automatically handles WAV headers in the response
• Provides metrics collection