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Overview

NVIDIA Riva provides two STT services:
  • RivaSTTService for real-time streaming transcription using Parakeet models
  • RivaSegmentedSTTService for segmented transcription using Canary models with advanced language support

API Reference

Complete API documentation and method details

NVIDIA Riva Docs

Official NVIDIA Riva ASR documentation

Example Code

Working example with NVIDIA services integration

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Installation

To use NVIDIA Riva services, install the required dependency: 
pip install "pipecat-ai[riva]"
You’ll also need to set up your NVIDIA API key as an environment variable: NVIDIA_API_KEY.
Get your API key from NVIDIA’s developer portal.

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Frames

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Input

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

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Output

  • InterimTranscriptionFrame - Real-time transcription updates (streaming only)
  • TranscriptionFrame - Final transcription results
  • ErrorFrame - Connection or processing errors

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Service Comparison

FeatureRivaSTTServiceRivaSegmentedSTTService
ProcessingReal-time streamingSegmented (VAD-based)
ModelParakeet CTC 1.1BCanary 1B
LatencyUltra-lowHigher (batch processing)
LanguagesEnglish-focusedMulti-language
Interim Results✅ Yes❌ No
Best ForReal-time conversationMulti-language accuracy

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Models

ModelService ClassDescriptionLanguages
parakeet-ctc-1.1b-asrRivaSTTServiceStreaming ASR optimized for low latencyEnglish (various accents)
canary-1b-asrRivaSegmentedSTTServiceMultilingual ASR with high accuracy15+ languages
See NVIDIA’s model cards for detailed performance metrics.

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Language Support

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RivaSTTService (Parakeet)

Primarily supports English with various regional accents:
  • Language.EN_US - English (US) - en-US

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RivaSegmentedSTTService (Canary)

Supports multiple languages:
Language CodeDescriptionService Codes
Language.EN_USEnglish (US)en-US
Language.EN_GBEnglish (UK)en-GB
Language.ESSpanishes-ES
Language.ES_USSpanish (US)es-US
Language.FRFrenchfr-FR
Language.DEGermande-DE
Language.ITItalianit-IT
Language.PT_BRPortuguese (Brazil)pt-BR
Language.JAJapaneseja-JP
Language.KOKoreanko-KR
Language.RURussianru-RU
Language.HIHindihi-IN
Language.ARArabicar-AR

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Usage Example

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Real-time Streaming (RivaSTTService)

Initialize the RivaSTTService and use it in a pipeline: 
from pipecat.services.riva.stt import RivaSTTService
from pipecat.transcriptions.language import Language

# Basic streaming configuration
stt = RivaSTTService(
    api_key=os.getenv("NVIDIA_API_KEY"),
    params=RivaSTTService.InputParams(
        language=Language.EN_US
    )
)

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

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Segmented Multi-language (RivaSegmentedSTTService)

Initialize the RivaSegmentedSTTService for segmented transcription: 
from pipecat.services.riva.stt import RivaSegmentedSTTService
from pipecat.audio.vad.silero import SileroVADAnalyzer

# Multi-language segmented transcription
stt = RivaSegmentedSTTService(
    api_key=os.getenv("NVIDIA_API_KEY"),
    params=RivaSegmentedSTTService.InputParams(
        language=Language.ES,  # Spanish
        profanity_filter=False,
        automatic_punctuation=True,
        boosted_lm_words=["inteligencia", "artificial"],
        boosted_lm_score=5.0
    )
)



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

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Dynamic Configuration

Make settings updates by pushing an STTUpdateSettingsFrame for either service: 
from pipecat.frames.frames import STTUpdateSettingsFrame

await task.queue_frame(STTUpdateSettingsFrame(
    language=Language.FR,  # Change to French
  )
)

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Advanced Configuration

Both services support advanced ASR parameters:

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Word Boosting

  • boosted_lm_words: List of domain-specific terms to emphasize
  • boosted_lm_score: Boost intensity (default: 4.0, recommended: 4.0-8.0)

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Audio Processing

  • profanity_filter: Filter inappropriate content
  • automatic_punctuation: Add punctuation automatically
  • verbatim_transcripts: Control transcript formatting

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Voice Activity Detection (Streaming only)

  • start_history: History frames for speech start detection
  • start_threshold: Confidence threshold for speech start
  • stop_threshold: Confidence threshold for speech end

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Metrics

  • Time to First Byte (TTFB) - Latency from audio segment to transcription
  • Processing Duration - Time spent processing each segment
Learn how to enable Metrics in your Pipeline.

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Additional Notes

  • Authentication: Uses NVIDIA Cloud Functions with Bearer token authentication
  • Real-time vs Batch: Choose streaming for conversation, segmented for accuracy and multi-language
  • VAD Requirement: Segmented service requires Voice Activity Detection in the pipeline
  • Custom Endpoints: Supports custom Riva server endpoints for on-premise deployments