task_categories:audio-classification task_categories:voice-activity-detection size_categories:1K<n<10K language:he license:other arxiv:2307.08720 region:us
---
license: other
task_categories:
- audio-classification
- voice-activity-detection
language:
- he
size_categories:
- 1K<n<10K

extra_gated_prompt:
  "You agree to the following license terms:
  
  This material and data is licensed under the terms of the Creative Commons Attribution 4.0
  International License (CC BY 4.0), The full text of the CC-BY 4.0 license is available at
  https://creativecommons.org/licenses/by/4.0/.
  

  Notwithstanding the foregoing, this material and data may only be used, modified and distributed for
  the express purpose of training AI models, and subject to the foregoing restriction. In addition, this
  material and data may not be used in order to create audiovisual material that simulates the voice or
  likeness of the specific individuals appearing or speaking in such materials and data (a “deep-fake”).
  To the extent this paragraph is inconsistent with the CC-BY-4.0 license, the terms of this paragraph
  shall govern.


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---


ivrit.ai is a database of Hebrew audio and text content.

**audio-base** contains the raw, unprocessed sources.

**audio-vad** contains audio snippets generated by applying Silero VAD (https://github.com/snakers4/silero-vad) to the base dataset.
v1 data is generated using silero-vad's default parameters.
v2 data is generated using min_speech_duration_ms=2000 (milliseconds), and max_speech_duration_s=30 (seconds).

**audio-transcripts** contains transcriptions for each snippet in the audio-vad dataset.

You can find the full list of sources in this dataset under https://www.ivrit.ai/en/credits.

Paper: https://arxiv.org/abs/2307.08720

If you use our datasets, the following quote is preferable:

```
@misc{marmor2023ivritai,
      title={ivrit.ai: A Comprehensive Dataset of Hebrew Speech for AI Research and Development}, 
      author={Yanir Marmor and Kinneret Misgav and Yair Lifshitz},
      year={2023},
      eprint={2307.08720},
      archivePrefix={arXiv},
      primaryClass={eess.AS}
}
```
