metadata

annotations_creators:
  - machine-generated
language_creators:
  - other
language:
  - eng
  - en
  - spa
  - es
  - ind
  - id
license: cc-by-4.0
multilinguality:
  - multilingual
source_datasets:
  - extended|common_voice
  - MLCommons/ml_spoken_words
task_categories:
  - automatic-speech-recognition
task_ids: []
pretty_name: Audio Keyword Spotting
tags:
  - other-keyword-spotting

Dataset Card for Audio Keyword Spotting

Table of Contents

Dataset Description

Homepage: https://sil.ai.org
Point of Contact: SIL AI email
Source Data: MLCommons/ml_spoken_words, trabina GitHub

Dataset Summary

The initial version of this dataset is a subset of MLCommons/ml_spoken_words, which is derived from Common Voice, designed for easier loading. Specifically, the subset consists of ml_spoken_words files filtered by the names and placenames transliterated in Bible translations, as found in trabina. For our initial experiment, we have focused only on English, Spanish, and Indonesian, three languages whose name spellings are frequently used in other translations. We anticipate growing this dataset in the future to include additional keywords and other languages as the experiment progresses.

Data Fields

file: strinrelative audio path inside the archive
is_valid: if a sample is valid
language: language of an instance.
speaker_id: unique id of a speaker. Can be "NA" if an instance is invalid
gender: speaker gender. Can be one of ["MALE", "FEMALE", "OTHER", "NAN"]
keyword: word spoken in a current sample
audio: a dictionary containing the relative path to the audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: dataset[0]["audio"] the audio file is automatically decoded and resampled to dataset.features["audio"].sampling_rate. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus, it is important to first query the sample index before the "audio" column, i.e. dataset[0]["audio"] should always be preferred over dataset["audio"][0]

Data Splits

The data for each language is splitted into train / validation / test parts.

Supported Tasks

Keyword spotting and spoken term search

Personal and Sensitive Information

The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers.

Licensing Information

The dataset is licensed under CC-BY 4.0 and can be used for academic research and commercial applications in keyword spotting and spoken term search.