Datasets:

philgzl
/

demand

license: cc-by-4.0
dataset_info:
  features:
    - name: audio
      dtype: audio
    - name: name
      dtype: string
configs:
  - config_name: default
    data_files:
      - split: 16k
        path: data/16k-*.parquet
      - split: 48k
        path: data/48k-*.parquet

DEMAND: Diverse Environments Multichannel Acoustic Noise Database

This is a mirror of the DEMAND: Diverse Environments Multichannel Acoustic Noise Database. The original files were segmented and converted from WAV to Opus to reduce the size and accelerate streaming.

Sampling rate: 16 kHz and 48 kHz
Channels: 1 (individual channels are distributed as separate files)
Format: Opus
Splits:
- 16k: 22.7 hours, 6800 segments (each channel is treated as a separate file)
- 48k: 24.0 hours, 7200 segments (each channel is treated as a separated file)
License: CC BY 4.0
Source: https://zenodo.org/records/1227121
Paper: The Diverse Environments Multi-channel Acoustic Noise Database (DEMAND): A database of multichannel environmental noise recordings

Usage

import io

import soundfile as sf
from datasets import Features, Value, load_dataset

for item in load_dataset(
    "philgzl/demand",
    split="16k",
    streaming=True,
    features=Features({"audio": Value("binary"), "name": Value("string")}),
):
    print(item["name"])
    buffer = io.BytesIO(item["audio"])
    x, fs = sf.read(buffer)
    # do stuff...

Citation

@inproceedings{thiemann2013demand,
  title = {The diverse environments multi-channel acoustic noise database ({DEMAND}): {A} database of multichannel environmental noise recordings},
  author = {Thiemann, Joachim and Ito, Nobutaka and Vincent, Emmanuel},
  booktitle = {Proc. ICA},
  pages = {035081},
  year = {2013},
}