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---
license: mit
task_categories:
- automatic-speech-recognition
- text-to-speech
language:
- en
- zh
---
# audio-testing
## Overview
This is a small, open dataset designed for quick validation of audio-related pipelines and applications, especially for **Text-to-Speech (TTS)** and **Speech-to-Text (STT)** systems.
It provides a few short, diverse audio clips and corresponding text transcripts, allowing developers to verify input/output handling, audio processing, and transcription logic without downloading large datasets.
## Contents
* 3 short audio samples (`.mp3`, `.wav`)
* `metadata.jsonl` file containing text transcripts and file references
| Field | Type | Description |
| ------- | ---------- | ----------------------- |
| `audio` | audio file | Raw audio data |
| `text` | string | Transcript of the audio |
## Example Usage
```typescript
async function fetchAudio(url: string): Promise<{
data: Buffer;
mimeType: string;
}> {
const response = await fetch(url);
if (!response.ok) {
throw new Error(`Failed to fetch audio: ${response.statusText}`);
}
const arrayBuffer = await response.arrayBuffer();
const data = Buffer.from(arrayBuffer);
const mimeType = response.headers.get("content-type") || "audio/wav";
return { data, mimeType };
}
const audioUrl = "https://huggingface.co/datasets/JacobLinCool/audio-testing/resolve/main/audio/audio-1.mp3";
const { data, mimeType } = await fetchAudio(audioUrl);
const transcription = await transcribe(data, mimeType);
const words = "this is a test audio generated by the model".split(" ");
// pass if WER < 10%
let matchCount = 0;
for (const word of words) {
if (transcription.includes(word)) {
matchCount++;
}
}
expect(matchCount / words.length).toBeGreaterThan(0.9);
```
Ideal for verifying:
* TTS model output alignment with ground-truth text
* STT transcription accuracy and error handling
* Audio I/O integration in pipelines or apps
## License
MIT License |