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Overview

Neuphonic provides high-quality text-to-speech synthesis with two implementations:
  • NeuphonicTTSService: WebSocket-based with real-time streaming and interruption support
  • NeuphonicHttpTTSService: HTTP-based with server-sent events.
NeuphonicTTSService is the recommended option for interactive applications requiring low latency.

API Reference

Complete API documentation and method details

Neuphonic Docs

Official Neuphonic TTS API documentation

Example Code

Working example with WebSocket streaming

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Installation

To use Neuphonic services, install the required dependencies: 
pip install "pipecat-ai[neuphonic]"
You’ll also need to set up your Neuphonic API key as an environment variable: NEUPHONIC_API_KEY.
Get your API key from the Neuphonic Console.

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Frames

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Input

  • TextFrame - Text content to synthesize into speech
  • TTSSpeakFrame - Text that should be spoken immediately
  • TTSUpdateSettingsFrame - Runtime configuration updates (voice, speed, etc.)
  • LLMFullResponseStartFrame / LLMFullResponseEndFrame - LLM response boundaries

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Output

  • TTSStartedFrame - Signals start of synthesis
  • TTSAudioRawFrame - Generated audio data chunks (streaming)
  • TTSStoppedFrame - Signals completion of synthesis
  • ErrorFrame - API or processing errors

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Service Comparison

FeatureNeuphonicTTSService (WebSocket)NeuphonicHttpTTSService (HTTP)
Streaming✅ Real-time chunks✅ Server-sent events
Interruption✅ Advanced handling❌ Limited support
Latency🚀 Ultra-low📈 Moderate

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Language Support

Neuphonic supports multiple languages with automatic base language detection:
Language CodeDescriptionService Code
Language.ENEnglishen
Language.ESSpanishes
Language.DEGermande
Language.NLDutchnl
Language.ARArabicar
Language.FRFrenchfr
Language.PTPortuguesept
Language.RURussianru
Language.HIHindihi
Language.ZHChinesezh
Regional variants (e.g., EN_US, ES_ES) are automatically mapped to their base language.

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Usage Example

Initialize the NeuphonicTTSService and use it in a pipeline: 
from pipecat.services.neuphonic.tts import NeuphonicTTSService
from pipecat.transcriptions.language import Language
import os

# Configure WebSocket service
tts = NeuphonicTTSService(
    api_key=os.getenv("NEUPHONIC_API_KEY"),
    voice_id="fc854436-2dac-4d21-aa69-ae17b54e98eb",  # Emily voice
    params=NeuphonicTTSService.InputParams(
        language=Language.EN,
        speed=1.2
    ),
    sample_rate=22050
)

# Use in pipeline
pipeline = Pipeline([
    transport.input(),
    stt,
    context_aggregator.user(),
    llm,
    tts,
    transport.output(),
    context_aggregator.assistant()
])

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HTTP Service

Initialize the NeuphonicHttpTTSService and use it in a pipeline: 
from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService

# For simpler, HTTP-based synthesis
http_tts = NeuphonicHttpTTSService(
    api_key=os.getenv("NEUPHONIC_API_KEY"),
    voice_id="your-voice-id",
    params=NeuphonicHttpTTSService.InputParams(
        language=Language.ES,
        speed=1.0
    )
)

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Dynamic Voice Switching

from pipecat.frames.frames import TTSUpdateSettingsFrame

# Change voice during conversation
await task.queue_frame(TTSUpdateSettingsFrame({
    "voice_id": "new-voice-id"
}))

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Metrics

Both services provide comprehensive metrics:
  • Time to First Byte (TTFB) - Latency from text input to first audio
  • Processing Duration - Total synthesis time
  • Character Usage - Text processed for billing
Learn how to enable Metrics in your Pipeline.

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Additional Notes

  • WebSocket Recommended: Use NeuphonicTTSService for real-time applications requiring low latency and interruption support