README.md

metadata

dataset_info:
  - config_name: large
    features:
      - name: audio
        dtype: audio
      - name: class
        dtype: string
      - name: class_id
        dtype: int64
      - name: noise_measurement
        dtype: float64
      - name: latitude
        dtype: float64
      - name: longitude
        dtype: float64
      - name: altitude
        dtype: float64
      - name: accuracy
        dtype: float64
      - name: submitter_id
        dtype: int64
      - name: timestamp
        dtype: string
    splits:
      - name: train
        num_bytes: 1878733113.914
        num_examples: 37634
    download_size: 1865541717
    dataset_size: 1878733113.914
  - config_name: small
    features:
      - name: audio
        dtype: audio
      - name: class
        dtype: string
      - name: class_id
        dtype: int64
      - name: noise_measurement
        dtype: int64
        id: nullable
      - name: latitude
        dtype: float64
      - name: longitude
        dtype: float64
      - name: altitude
        dtype: float64
      - name: accuracy
        dtype: float64
      - name: submitter_id
        dtype: int64
      - name: timestamp
        dtype: string
    splits:
      - name: train
        num_bytes: 49675307.833
        num_examples: 1001
    download_size: 49577542
    dataset_size: 49675307.833
configs:
  - config_name: large
    data_files:
      - split: train
        path: large/train-*
  - config_name: small
    data_files:
      - split: train
        path: small/train-*
task_categories:
  - audio-classification
tags:
  - audio
  - text
size_categories:
  - 10K<n<100K

The urban-noise dataset consists of audio samples representing urban noise environments. It is designed for tasks such as noise classification, audio tagging, or machine learning applications in sound analysis. The dataset includes two configurations, large and small, with varying sizes of data.

Example Usage

from datasets import load_dataset

# Load the large configuration
large_dataset = load_dataset("Sunbird/urban-noise", "large")

# Load the small configuration
small_dataset = load_dataset("Sunbird/urban-noise", "small")