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Overview

DeepgramSTTService provides real-time speech recognition using Deepgram’s WebSocket API with support for interim results, language detection, and voice activity detection (VAD).

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Installation

To use DeepgramSTTService, install the required dependencies:

pip install "pipecat-ai[deepgram]"

You’ll also need to set up your Deepgram API key as an environment variable: DEEPGRAM_API_KEY.

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Frames

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Input

• InputAudioRawFrame - Raw PCM audio data (16-bit, 16kHz, mono)
• STTUpdateSettingsFrame - Runtime transcription configuration updates
• STTMuteFrame - Mute audio input for transcription

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Output

• InterimTranscriptionFrame - Real-time transcription updates
• TranscriptionFrame - Final transcription results
• ErrorFrame - Connection or processing errors

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Language Support

Deepgram STT supports the following languages and regional variants:

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Usage Example

from pipecat.services.deepgram.stt import DeepgramSTTService
from deepgram import LiveOptions
from pipecat.transcriptions.language import Language

# Configure service
stt = DeepgramSTTService(
    api_key="your-api-key",
    live_options=LiveOptions(
        model="nova-3-general",
        language="en-US",
        smart_format=True
    )
)

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

# Change language dynamically
await stt.set_language(Language.FR)

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Metrics

The service provides:

• Time to First Byte (TTFB) - Latency from audio input to first transcription
• Processing Duration - Total time spent processing audio

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Additional Notes

• Connection Management: Automatically handles WebSocket connections and reconnections
• VAD Integration: Supports Deepgram’s built-in VAD, though we recommend using local VAD services like Silero for better performance
• Sample Rate: Can be configured per service, but we recommend setting it globally in PipelineParams for consistency across services