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Overview

DeepgramSTTService provides real-time speech-to-text capabilities using Deepgram’s WebSocket API. It supports 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.

You can obtain a Deepgram API key by signing up at Deepgram.

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Configuration

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Constructor Parameters

api_key
str
required

Your Deepgram API key

url
str
default: ""

Custom Deepgram API endpoint URL

live_options
LiveOptions

Custom transcription options

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Default Options

LiveOptions(
    encoding="linear16",
    language=Language.EN,
    model="nova-2-general",
    sample_rate=16000,
    channels=1,
    interim_results=True,
    smart_format=True,
    punctuate=True,
    profanity_filter=True,
    vad_events=False
)

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Input

The service processes InputAudioRawFrame instances containing:

  • Raw PCM audio data
  • 16-bit depth
  • 16kHz sample rate
  • Single channel (mono)

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Output Frames

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TranscriptionFrame

Generated for final transcriptions, containing:

text
string

Transcribed text

user_id
string

User identifier

timestamp
string

ISO 8601 formatted timestamp

language
Language

Detected language (if available)

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InterimTranscriptionFrame

Generated during ongoing speech, containing same fields as TranscriptionFrame but with preliminary results.

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Methods

See the STT base class methods for additional functionality.

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Language Setting

await service.set_language(Language.FR)

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Model Selection

await service.set_model("nova-2-general")

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Usage Example

from pipecat.services.deepgram import DeepgramSTTService
from deepgram import LiveOptions

# Configure service
stt_service = DeepgramSTTService(
    api_key="your-api-key",
    live_options=LiveOptions(
        model="nova-2-general",
        language="en-US",
        smart_format=True,
        vad_events=True
    )
)

# Use in pipeline
pipeline = Pipeline([
    transport.input(),   # Produces InputAudioRawFrame
    stt_service,         # Processes audio → produces transcription frames
    text_handler         # Consumes transcription frames
])

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Language Support

Deepgram STT supports the following languages and regional variants:

Language CodeDescriptionService Codes
Language.BGBulgarianbg
Language.CACatalanca
Language.ZHChinese (Mandarin, Simplified)zh, zh-CN, zh-Hans
Language.ZH_TWChinese (Mandarin, Traditional)zh-TW, zh-Hant
Language.ZH_HKChinese (Cantonese, Traditional)zh-HK
Language.CSCzechcs
Language.DADanishda, da-DK
Language.NLDutchnl
Language.NL_BEDutch (Flemish)nl-BE
Language.ENEnglishen
Language.EN_USEnglish (US)en-US
Language.EN_AUEnglish (Australia)en-AU
Language.EN_GBEnglish (UK)en-GB
Language.EN_NZEnglish (New Zealand)en-NZ
Language.EN_INEnglish (India)en-IN
Language.ETEstonianet
Language.FIFinnishfi
Language.FRFrenchfr
Language.FR_CAFrench (Canada)fr-CA
Language.DEGermande
Language.DE_CHGerman (Switzerland)de-CH
Language.ELGreekel
Language.HIHindihi
Language.HUHungarianhu
Language.IDIndonesianid
Language.ITItalianit
Language.JAJapaneseja
Language.KOKoreanko, ko-KR
Language.LVLatvianlv
Language.LTLithuanianlt
Language.MSMalayms
Language.NONorwegianno
Language.PLPolishpl
Language.PTPortuguesept
Language.PT_BRPortuguese (Brazil)pt-BR
Language.PT_PTPortuguese (Portugal)pt-PT
Language.RORomanianro
Language.RURussianru
Language.SKSlovaksk
Language.ESSpanishes, es-419
Language.SVSwedishsv, sv-SE
Language.THThaith, th-TH
Language.TRTurkishtr
Language.UKUkrainianuk
Language.VIVietnamesevi

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Special Features

  • Supports multilingual transcription (Spanish + English) using multi
  • Provides multiple regional variants for major languages
  • Supports traditional and simplified Chinese scripts

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Usage Example

# Configure service with specific language
stt_service = DeepgramSTTService(
    api_key="your-api-key",
    live_options=LiveOptions(
        language="en-US",  # Specific regional variant
        model="nova-2-general"
    )
)

Note: Language support may vary by model. Check Deepgram’s documentation for model-specific language availability.

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Frame Flow

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Metrics Support

The service supports metrics collection when VAD is enabled:

  • Time to First Byte (TTFB)
  • Processing duration
  • Speech detection events

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Notes

  • Requires valid Deepgram API key
  • Supports real-time transcription
  • Handles WebSocket connection management
  • Provides language detection
  • Supports model switching
  • Includes VAD capabilities
  • Manages connection lifecycle
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