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| title: README | |
| emoji: 🌍 | |
| colorFrom: gray | |
| colorTo: yellow | |
| sdk: static | |
| pinned: false | |
| license: other | |
| ivrit.ai is an effort to provide high-quality Hebrew datasets under a permissive license. | |
| It is our hope that such datasets will be used to enable first-class support for Hebrew in AI models. | |
| More about us can be found at ivrit.ai. | |
| We are proud to present our latest achievements: | |
| 1) A state-of-the-art Hebrew speech-to-text model: https://huggingface.co/ivrit-ai/whisper-large-v3-ct2 | |
| 2) A turbo-based Hebrew speech-to-text model: https://huggingface.co/ivrit-ai/whisper-large-v3-turbo-ct2 | |
| 3) Our newest comprehensive Hebrew language dataset: https://huggingface.co/datasets/ivrit-ai/crowd-transcribe-v5 | |
| Paper: https://www.isca-archive.org/interspeech_2025/marmor25_interspeech.pdf | |
| If you use our datasets or models, the following quote is preferable: | |
| ``` | |
| @inproceedings{marmor2025building, | |
| title={Building an Accurate Open-Source Hebrew ASR System through Crowdsourcing}, | |
| author={Marmor, Yanir and Lifshitz, Yair and Snapir, Yoad and Misgav, Kinneret}, | |
| booktitle={Proc. Interspeech 2025}, | |
| pages={723--727}, | |
| year={2025} | |
| } | |
| ``` |