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--- |
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language: |
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- eng |
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pretty_name: Unsupervised Peoples Speech |
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tags: |
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- audio |
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- unsupervised |
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task_categories: |
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- automatic-speech-recognition |
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- audio-classification |
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task_ids: |
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- audio-language-identification |
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viewer: false |
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--- |
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# Dataset Card for Unsupervised Peoples Speech |
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## Table of Contents |
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- [Dataset Card for Unuspervised Peoples Speech](#dataset-card-for-unsupervised-peoples-speech) |
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Relevant Statistics](#relevant-statistics) |
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- [Dataset Structure](#dataset-structure) |
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- [Audio folders](#audio-folders) |
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- [Dataset Creation](#dataset-creation) |
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- [Source Data](#source-data) |
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- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) |
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- [Preprocessing](#preprocessing) |
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- [Annotations] (#annotations) |
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- [Annotation Process] (#annotation-process) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Additional Information](#additional-information) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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## Dataset Description |
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- **Point of Contact:** [[email protected]](mailto:[email protected]) |
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### Dataset Summary |
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The Unsupervised Peoples Speech Dataset is a compilation of audiofiles extracted from Archive.org that is licensed for academic and commercial usage under CC-BY and CC-BY-SA licenses. It includes more than one million hours of audio with a diverse set of speakers. |
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### Relevant Statistics |
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#### Duration Distribution |
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Most of the audios range between 1 and 10 minutes in length, with only 14 of them exceeding the 100 hour mark. |
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#### Sample Rates |
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99% of the audio in the dataset has a 44.1Khz sample rate, and the remaining audio varies from the more common 16Khz, 24Khz and 48 Khz to custom sample rates. |
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## Dataset Structure |
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### Audio folders |
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Folders with the raw audio. We split this into two directories because Hugging Face does not support more than 10,000 files in a single directory. |
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## Dataset Creation |
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### Source Data |
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#### Initial Data Collection and Normalization |
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Data was downloaded via the archive.org API. No data inference was done. |
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#### Preprocessing |
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No preprocessing was done. |
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### Annotations |
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#### Annotation process |
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No manual annotation is done. We download only source audio. |
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In particular, there is no "forced alignment" or "segmentation" done on this dataset. |
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### Personal and Sensitive Information |
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Several of our sources are legal and government proceedings, spoken stories, speeches, and so on. Given that these were intended as public documents and licensed as such, it is natural that the involved individuals are aware of this. |
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## Considerations for Using the Data |
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### Discussion of Biases |
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Our data is downloaded from archive.org. As such, the data is biased towards whatever users decide to upload there. |
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Almost all of our data is American accented English. |
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## Additional Information |
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### Licensing Information |
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The source data contains data under CC-BY-SA and CC-BY licenses. |
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We license this dataset under https://creativecommons.org/licenses/by-sa/4.0/ |
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### Citation Information |
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Please cite |
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``` |
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@article{USP, |
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author={Daniel Galvez and |
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Ryan Hileman and |
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Rafael Mosquera and |
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Juan Ciro and |
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Kurt Bollacker and |
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Peter Mattson and |
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David Kanter}, |
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title = {Unsupervised People's Speech (The Million Hour Audio Dataset)}, |
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year = {2023}, |
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url = {https://huggingface.co/datasets/MLCommons/peoples_speech}, |
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} |
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``` |
