|
|
--- |
|
|
license: cc-by-sa-4.0 |
|
|
task_categories: |
|
|
- automatic-speech-recognition |
|
|
language: |
|
|
- en |
|
|
pretty_name: Numb3rs_ds |
|
|
size_categories: |
|
|
- 10K<n<100K |
|
|
configs: |
|
|
- config_name: default |
|
|
data_files: |
|
|
- split: test |
|
|
path: metadata.jsonl |
|
|
--- |
|
|
|
|
|
# Numb3rs - Numbers Speech Benchmark (Dataset) |
|
|
|
|
|
A speech dataset for text normalization (TN) and inverse text normalization (ITN) tasks, containing paired written/spoken forms with corresponding synthetic audio. |
|
|
|
|
|
## Dataset Creation |
|
|
|
|
|
This dataset was created through the following pipeline: |
|
|
|
|
|
1. **Source Data**: Text normalization pairs were derived from the [Google Text Normalization dataset](https://www.kaggle.com/datasets/google-nlu/text-normalization), containing written forms (e.g., "$100") and their spoken equivalents (e.g., "one hundred dollars"). |
|
|
|
|
|
2. **Audio Generation**: Audio was synthesized using [**Magpie TTS**](https://build.nvidia.com/nvidia/magpie-tts-multilingual/modelcard) (NVIDIA's expressive multilingual text-to-speech model), with utterances distributed across **6 predefined voices** to ensure speaker diversity. |
|
|
|
|
|
3. **Human Verification**: All generated samples were manually verified by human annotators. Only entities that passed quality review were retained in the final dataset. |
|
|
|
|
|
## Dataset Statistics |
|
|
|
|
|
| Category | Samples | Total Duration | Avg Duration | Description | |
|
|
|----------|---------|----------------|--------------|-------------| |
|
|
| ADDRESS | 885 | 18.7 min | 1.26s | Highway/road identifiers (e.g., "A6" → "a six") | |
|
|
| CARDINAL | 780 | 14.5 min | 1.11s | Cardinal numbers (e.g., "42" → "forty two") | |
|
|
| DATE | 977 | 30.6 min | 1.88s | Date expressions (e.g., "Jan 1, 2020" → "january first twenty twenty") | |
|
|
| DECIMAL | 928 | 24.9 min | 1.61s | Decimal numbers (e.g., "3.14" → "three point one four") | |
|
|
| DIGIT | 771 | 17.8 min | 1.39s | Digit sequences (e.g., "123" → "one two three") | |
|
|
| FRACTION | 884 | 23.4 min | 1.59s | Fractional values (e.g., "1/2" → "one half") | |
|
|
| MEASURE | 914 | 27.7 min | 1.82s | Measurements (e.g., "5 kg" → "five kilograms") | |
|
|
| MONEY | 775 | 26.8 min | 2.07s | Currency amounts (e.g., "$100" → "one hundred dollars") | |
|
|
| ORDINAL | 957 | 14.3 min | 0.90s | Ordinal numbers (e.g., "1st" → "first") | |
|
|
| PLAIN | 377 | 9.6 min | 1.52s | Plain number words | |
|
|
| TELEPHONE | 936 | 61.3 min | 3.93s | Phone numbers | |
|
|
| TIME | 947 | 24.1 min | 1.53s | Time expressions (e.g., "3:00 PM" → "three o'clock p m") | |
|
|
| **TOTAL** | **10,131** | **4.89h** | **1.74s** | | |
|
|
|
|
|
## Usage |
|
|
|
|
|
```python |
|
|
from datasets import load_dataset |
|
|
|
|
|
dataset = load_dataset("NNstuff/Numb3rs") |
|
|
``` |
|
|
|
|
|
## Metadata Schema |
|
|
|
|
|
| Field | Type | Description | |
|
|
|-------|------|-------------| |
|
|
| `file_name` | string | Relative path to audio file | |
|
|
| `name` | string | Original sample identifier | |
|
|
| `duration` | float | Audio duration in seconds | |
|
|
| `category` | string | Category name (e.g., "MONEY", "DATE") | |
|
|
| `original_text` | string | Written form (TN input) | |
|
|
| `text` | string | Spoken form (ITN input) | |
|
|
| `lang` | string | Language code ("en") | |
|
|
|
|
|
## License |
|
|
|
|
|
CC-BY-SA-4.0 |
|
|
|
