The dataset viewer is not available for this subset.
Exception: ConnectionError
Message: Couldn't reach 'NNstuff/Numb3rs' on the Hub (LocalEntryNotFoundError)
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 343, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 268, in get_dataset_config_info
builder = load_dataset_builder(
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1132, in load_dataset_builder
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1031, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 953, in dataset_module_factory
raise ConnectionError(f"Couldn't reach '{path}' on the Hub ({e.__class__.__name__})") from e
ConnectionError: Couldn't reach 'NNstuff/Numb3rs' on the Hub (LocalEntryNotFoundError)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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:
Source Data: Text normalization pairs were derived from the Google Text Normalization dataset, containing written forms (e.g., "$100") and their spoken equivalents (e.g., "one hundred dollars").
Audio Generation: Audio was synthesized using Magpie TTS (NVIDIA's expressive multilingual text-to-speech model), with utterances distributed across 6 predefined voices to ensure speaker diversity.
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
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
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