Prompt Chain

Test Audio Transcription with ElevenLabs

Promptfoo example that tests ElevenLabs speech-to-text with WER scoring, speaker diarization, and cost and latency checks.

Works with elevenlabs

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Updated 10 days ago
Source checked Sep 10, 2026
Version 0.123.0

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Why it matters

Automate the testing of audio transcription services using the ElevenLabs STT provider. Ensure the accuracy and reliability of your speech-to-text capabilities.

Outcomes

What it gets done

01

Configure ElevenLabs STT for transcription testing.

02

Process audio files for transcription.

03

Evaluate the quality of transcribed text.

04

Integrate transcription testing into CI/CD pipelines.

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/pfoo-elevenlabs-stt | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

Elevenlabs Stt

This promptfoo example runs audio through ElevenLabs' Speech-to-Text API and scores the result with Word Error Rate, speaker diarization, and cost and latency assertions, using config-, prompt-, or vars-level audio input. Use it to regression-test an ElevenLabs STT integration's accuracy, diarization, cost, and latency; it requires a real ElevenLabs API key and account.

What it does

This is a promptfoo example (provider-elevenlabs/stt) for testing ElevenLabs' Speech-to-Text API as a promptfoo provider. It runs audio files through the eleven_speech_to_text_v1 model and lets you assert on the results: automatic Word Error Rate (WER) calculation against a reference transcript, with substitutions, deletions, insertions, and a per-word breakdown; speaker diarization, labeling and timestamping up to a configurable number of distinct speakers; cost and latency thresholds; and content assertions (contains/not-contains on the transcribed text, or custom JavaScript assertions on WER or speaker count). Audio can be supplied at the config, prompt, or test-vars level, and the provider supports MP3, WAV, FLAC, M4A, OGG, Opus, and WebM.

When to use - and when NOT to

Use it as a template when you need to benchmark or regression-test an STT integration: comparing transcription accuracy across audio qualities or languages, verifying diarization correctly separates speakers, or gating a build on cost, latency, or WER thresholds. It needs an ELEVENLABS_API_KEY and real ElevenLabs usage - the free tier covers 1 hour/month, paid tiers run about $0.10 per minute - so it's not a fit for testing without an ElevenLabs account, and WER comparisons are only meaningful when the reference text exactly matches the audio, including punctuation.

Inputs and outputs

Inputs: one or more audio files, via audioFile config, a prompt list, or vars, plus config like modelId, language (ISO 639-1, or omitted for auto-detect), diarization/maxSpeakers, and referenceText/calculateWER. Output is the transcription text plus, when enabled, a diarization array (per-speaker segments with start and end times and confidence) and a wer metrics object (error rate, substitution/deletion/insertion counts, and an aligned reference-vs-hypothesis diff) available to test assertions via context.vars.metadata.

Integrations

  • promptfoo eval framework, run via npx promptfoo@latest eval
  • ElevenLabs Speech-to-Text API (eleven_speech_to_text_v1), 30+ languages
  • Cost and latency assertion types built into promptfoo
  • Related promptfoo examples: ElevenLabs TTS and ElevenLabs Isolation for audio cleanup
  • Config options cover baseUrl, request timeout (default 120000ms), and retries (default 3), so the provider can point at a non-default endpoint or tolerate flaky connections

Troubleshooting notes in the example cover a missing ELEVENLABS_API_KEY, unsupported audio formats (convert with ffmpeg), and unexpectedly high WER on clear audio - usually a reference-text mismatch, wrong auto-detected language, or background noise, since the WER calculation normalizes case and punctuation before comparing.

Who it's for

Teams building or evaluating a voice product who want a promptfoo-based way to regression-test ElevenLabs transcription accuracy, speaker diarization, cost, and latency before shipping.

Source README

provider-elevenlabs/stt (ElevenLabs Speech-to-Text)

This example demonstrates how to use ElevenLabs STT provider for audio transcription testing.

Quick Start

npx promptfoo@latest init --example provider-elevenlabs/stt
cd provider-elevenlabs/stt
export ELEVENLABS_API_KEY=your_api_key_here
npx promptfoo@latest eval

Features

  • Audio Transcription: Convert speech to text with high accuracy
  • Speaker Diarization: Identify and separate multiple speakers in audio
  • Word Error Rate (WER): Measure transcription accuracy against reference text
  • Multi-format Support: MP3, WAV, FLAC, M4A, OGG, OPUS, WebM

Setup

  1. Set your API key:

    export ELEVENLABS_API_KEY=your_api_key_here
    
  2. Prepare audio files:
    Create an audio/ directory with your test audio files:

    mkdir -p audio
    # Place your audio files in the audio/ directory
    
  3. Run the evaluation:

    promptfoo eval
    

Configuration

Basic Transcription

providers:
  - id: elevenlabs:stt:basic
    config:
      modelId: eleven_speech_to_text_v1
      language: en # ISO 639-1 language code

Speaker Diarization

Identify and label different speakers in your audio:

providers:
  - id: elevenlabs:stt:diarization
    config:
      modelId: eleven_speech_to_text_v1
      diarization: true
      maxSpeakers: 3 # Optional: hint for expected number of speakers

The response will include speaker segments:

{
  "text": "Full transcription...",
  "diarization": [
    {
      "speaker_id": "speaker_0",
      "text": "Hello, how are you?",
      "start_time_ms": 0,
      "end_time_ms": 2500,
      "confidence": 0.95
    },
    {
      "speaker_id": "speaker_1",
      "text": "I'm doing well, thanks!",
      "start_time_ms": 2500,
      "end_time_ms": 5000,
      "confidence": 0.92
    }
  ]
}

Accuracy Testing with WER

Word Error Rate (WER) measures transcription accuracy. Lower is better (0 = perfect).

providers:
  - id: elevenlabs:stt:accuracy
    config:
      modelId: eleven_speech_to_text_v1
      calculateWER: true
      referenceText: The quick brown fox jumps over the lazy dog

WER Formula: (Substitutions + Deletions + Insertions) / Total Words

The response includes detailed WER metrics:

{
  "wer": 0.05, // 5% error rate
  "substitutions": 1,
  "deletions": 0,
  "insertions": 0,
  "correct": 19,
  "totalWords": 20,
  "details": {
    "reference": "the quick brown fox jumps",
    "hypothesis": "the quick green fox jumps",
    "alignment": "REF: the quick brown fox jumps\nHYP: the quick green fox jumps\nOPS:           SSSSS"
  }
}

WER Interpretation:

  • 0.00 - 0.05: Excellent (95%+ accurate)
  • 0.05 - 0.10: Good (90-95% accurate)
  • 0.10 - 0.20: Fair (80-90% accurate)
  • 0.20+: Poor (< 80% accurate)

Supported Audio Formats

Format Extension Notes
MP3 .mp3 Widely compatible
MP4 Audio .mp4, .m4a AAC/MPEG-4 audio
WAV .wav Uncompressed, high quality
FLAC .flac Lossless compression
OGG .ogg Open format
Opus .opus Modern, efficient codec
WebM .webm Web-optimized

Audio Input Methods

Method 1: Config-level

providers:
  - id: elevenlabs:stt
    config:
      audioFile: path/to/audio.mp3

Method 2: Prompt-level

prompts:
  - audio/sample1.mp3
  - audio/sample2.wav

Method 3: Vars-level

tests:
  - vars:
      audioFile: audio/sample.mp3

Testing Assertions

Cost Threshold

tests:
  - assert:
      - type: cost
        threshold: 0.05 # Max $0.05 per transcription

Latency Threshold

tests:
  - assert:
      - type: latency
        threshold: 10000 # Max 10 seconds

Transcription Quality

tests:
  - assert:
      - type: contains
        value: expected phrase

      - type: not-contains
        value: incorrect phrase

WER Threshold

tests:
  - assert:
      - type: javascript
        value: |
          const wer = context.vars.metadata?.wer?.wer || 1;
          wer < 0.1  // Less than 10% error

Speaker Count

tests:
  - assert:
      - type: javascript
        value: |
          const diarization = context.vars.metadata?.transcription?.diarization || [];
          const uniqueSpeakers = new Set(diarization.map(s => s.speaker_id));
          uniqueSpeakers.size === 2  // Expect 2 speakers

Language Support

ElevenLabs STT supports 30+ languages. Specify using ISO 639-1 codes:

config:
  language: en # English
  # language: es  # Spanish
  # language: fr  # French
  # language: de  # German
  # language: it  # Italian
  # language: pt  # Portuguese
  # language: ja  # Japanese
  # language: ko  # Korean
  # language: zh  # Chinese

Auto-detection: Omit language to let the API detect the language automatically.

Cost Information

STT pricing is based on audio duration:

  • Free tier: 1 hour/month
  • Paid tiers: $0.10 per minute ($0.00167 per second)

The provider automatically tracks and reports costs in the evaluation results.

Advanced Usage

Batch Transcription

prompts:
  - audio/batch1.mp3
  - audio/batch2.mp3
  - audio/batch3.mp3

providers:
  - id: elevenlabs:stt
    config:
      modelId: eleven_speech_to_text_v1

# Test all files with consistent assertions
tests:
  - assert:
      - type: cost
        threshold: 0.10
      - type: latency
        threshold: 15000

Multi-language Testing

providers:
  - id: elevenlabs:stt:english
    config:
      language: en

  - id: elevenlabs:stt:spanish
    config:
      language: es

  - id: elevenlabs:stt:autodetect
    config:
      # No language specified = auto-detect

prompts:
  - audio/english_sample.mp3
  - audio/spanish_sample.mp3

Accuracy Comparison

Compare transcription accuracy across different audio qualities:

prompts:
  - audio/high_quality_48khz.wav
  - audio/medium_quality_16khz.mp3
  - audio/low_quality_8khz.mp3

providers:
  - id: elevenlabs:stt
    config:
      calculateWER: true
      referenceText: This is the expected transcription text

tests:
  - description: High quality should have WER < 5%
    vars:
      audioFile: audio/high_quality_48khz.wav
    assert:
      - type: javascript
        value: (context.vars.metadata?.wer?.wer || 1) < 0.05

  - description: Medium quality should have WER < 10%
    vars:
      audioFile: audio/medium_quality_16khz.mp3
    assert:
      - type: javascript
        value: (context.vars.metadata?.wer?.wer || 1) < 0.10

Troubleshooting

API Key Issues

# Verify your API key is set
echo $ELEVENLABS_API_KEY

# Or set it inline
ELEVENLABS_API_KEY=your_key promptfoo eval

Audio File Not Found

Error: Failed to read audio file: ENOENT: no such file or directory

Solution: Use absolute paths or paths relative to the config file:

prompts:
  - /absolute/path/to/audio.mp3
  - ./relative/path/to/audio.mp3

Unsupported Format

Error: Unsupported audio format

Solution: Convert your audio to a supported format (MP3, WAV, etc.) using tools like ffmpeg:

ffmpeg -i input.video -vn -acodec mp3 output.mp3

High WER on Clear Audio

If you're getting unexpectedly high WER:

  1. Check reference text - ensure it exactly matches the audio (including punctuation)
  2. Specify language - auto-detection may choose the wrong language
  3. Audio quality - ensure audio is clear with minimal background noise
  4. Normalization - WER calculation normalizes text (lowercase, removes punctuation)

API Reference

Config Options

Option Type Default Description
modelId string eleven_speech_to_text_v1 STT model to use
language string auto-detect ISO 639-1 language code
diarization boolean false Enable speaker identification
maxSpeakers number - Expected number of speakers
audioFile string - Path to audio file
audioFormat string auto-detect Audio format override
referenceText string - Expected transcription for WER
calculateWER boolean false Calculate Word Error Rate
baseUrl string https://api.elevenlabs.io/v1 API endpoint
timeout number 120000 Request timeout (ms)
retries number 3 Number of retry attempts

Related Examples

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FAQ

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