Datasets:
Tasks:
Audio Classification
Modalities:
Audio
Formats:
soundfolder
Languages:
English
Size:
1K - 10K
License:
Search is not available for this dataset
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SAM Wake Word Dataset
Audio dataset for training a wake-word detection model to recognise the keyword "Sam".
Dataset Description
Each sample is a short audio clip labelled as either positive (contains the wake word) or negative (does not).
| Split | Description |
|---|---|
positive/ |
Clips of the word "Sam" spoken in varied styles, speeds, and intonations |
negative/ |
Clips of phonetically similar or common words that are not "Sam" |
Generation
All audio is synthesised using OpenAI gpt-4o-mini-tts with:
- 10 voices: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer
- Variable speed: 0.85× – 1.30×
- Diverse speaking styles: whispering, shouting, questioning, commanding, accented, etc.
Positive prompts include: "Sam", "sam", "SAM", "Sam!", "Hey Sam", "Yo Sam"
Negative prompts include phonetically close words (ham, jam, slam, spam, dam, same, samuel, sample) and common short words (hello, hey, stop, play, yes, no, …).
Audio Format
- Sample rate: 16 kHz
- Channels: mono
- Format: WAV
Manifest
A manifest.json file is included with metadata for each clip:
{
"file": "positive/positive_00042.wav",
"label": "positive",
"text": "Sam",
"voice": "nova",
"speed": 1.12
}
Usage
from datasets import load_dataset
ds = load_dataset("quo-labs/sam-wake-word")
License
MIT
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