AudioBreakageScorer
Scorer for evaluating audio breakage and technical quality in TTS-generated speech.
Overview
Scorer for evaluating audio breakage and technical quality in TTS-generated speech.
Use Cases
- General AI evaluation and quality assessment
How It Works
This scorer uses LLM-as-Judge technology to evaluate responses. It prompts a large language model with specific evaluation criteria and the content to assess, then analyzes the LLM's judgment to produce a score and detailed reasoning.
Input Schema
| Parameter | Type | Required | Description |
|---|
Output Schema
| Field | Type | Description |
|---|---|---|
| score | any | - |
| passed | any | - |
| reasoning | any | - |
| metadata | any | - |
Score Interpretation
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Frequently Asked Questions
When should I use this scorer?
Use AudioBreakageScorer when you need to evaluate audio aspects of your AI outputs. It's particularly useful for general ai evaluation and quality assessment.
Why doesn't this scorer need expected output?
This scorer evaluates without a reference answer by using the specific input fields listed in its schema. Those fields are evidence for the check; they are not automatically factual ground truth.
Can I customize the threshold?
This scorer's displayed default threshold is 7. Where the eval-job configuration exposes a threshold, review it against the scorer's native scale before saving. The stored pass decision uses that scorer-specific configuration.
Quick Info
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