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--- |
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license: cc-by-4.0 |
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size_categories: |
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- 1M<n<10M |
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configs: |
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- config_name: pre |
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data_files: |
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- pre/*/*.arrow |
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- config_name: raw |
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data_files: |
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- raw/*/*.arrow |
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- config_name: GK |
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data_files: |
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- pre/geekonomy/*.arrow |
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- raw/geekonomy/*.arrow |
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- config_name: GK_pre |
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data_files: pre/geekonomy/*.arrow |
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- config_name: GK_raw |
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data_files: raw/geekonomy/*.arrow |
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- config_name: OH |
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data_files: |
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- pre/osim-history/*.arrow |
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- raw/osim-history/*.arrow |
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- config_name: OH_pre |
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data_files: pre/osim-history/*.arrow |
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- config_name: OH_raw |
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data_files: raw/osim-history/*.arrow |
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- config_name: DK |
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data_files: |
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- pre/dor/*.arrow |
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- raw/dor/*.arrow |
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- config_name: DK_pre |
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data_files: pre/dor/*.arrow |
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- config_name: DK_raw |
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data_files: raw/dor/*.arrow |
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- config_name: YO |
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data_files: |
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- pre/Yo_the_podcast/*.arrow |
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- raw/Yo_the_podcast/*.arrow |
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- config_name: YO_pre |
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data_files: pre/Yo_the_podcast/*.arrow |
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- config_name: YO_raw |
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data_files: raw/Yo_the_podcast/*.arrow |
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- config_name: YV |
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data_files: |
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- pre/Yad_vashem/*.arrow |
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- raw/Yad_vashem/*.arrow |
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- config_name: YV_pre |
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data_files: pre/Yad_vashem/*.arrow |
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- config_name: YV_raw |
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data_files: raw/Yad_vashem/*.arrow |
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--- |
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# HebDB |
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**Paper:** http://arxiv.org/abs/2407.07566 |
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If you use our datasets, please use the following: |
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``` |
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@article{turetzky2024hebdb, |
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title={HebDB: a Weakly Supervised Dataset for Hebrew Speech Processing}, |
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author={Turetzky, Arnon and Tal, Or and Segal-Feldman, Yael and Dissen, Yehoshua and Zeldes, Ella and Roth, Amit and Cohen, Eyal and Shrem, Yosi and Chernyak, Bronya R and Seleznova, Olga and others}, |
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journal={arXiv preprint arXiv:2407.07566}, |
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year={2024} |
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} |
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``` |
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### Dataset Summary |
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A weakly supervised dataset for spoken language processing in the Hebrew language. HEBDB offers roughly 2500 hours of natural and spontaneous speech recordings in the Hebrew language, consisting of a large variety of speakers and topics. We provide raw recordings together with a pre-processed, weakly supervised, and filtered version. The goal of HEBDB is to further enhance research and development of spoken language processing tools for the Hebrew language. |
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Data variants are: `pre`, `raw`. Note variants share the same columns to ease the usage of dataset subsets but `raw` only use the columns: `fname`, `audio` and `is_raw`. |
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#### How do I download this? |
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##### Using 🤗 Datasets |
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```python |
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from datasets import load_dataset |
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# pre only |
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hebdb_pre = load_dataset("SLPRL-HUJI/HebDB", "pre") |
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# raw only |
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hebdb_raw = load_dataset("SLPRL-HUJI/HebDB", "raw") |
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# One specific source(see code list below), both raw and pre |
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geekonomy = load_dataset("SLPRL-HUJI/HebDB", "GK") |
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# One specific source, both raw and pre |
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geekonomy_pre = load_dataset("SLPRL-HUJI/HebDB", "GK_pre") |
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``` |
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To avoid downloading the entire dataset you can load it in streaming mode using `streaming=True`, for example: |
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```python |
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hebdb_pre = load_dataset("SLPRL-HUJI/HebDB", "pre", streaming=True) |
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``` |
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You can also load and mix: |
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```python |
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from datasets import concatenate_datasets, load_dataset |
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geekonomy = load_dataset("SLPRL-HUJI/HebDB", "GK_pre") |
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osim_history = load_dataset("SLPRL-HUJI/HebDB", "OH_pre") |
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# Concatenate both datasets |
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concatenated = concatenate_datasets([geekonomy, osim_history]) |
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``` |
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### Sources |
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The 6 available sources are reported in the table below. |
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| code | name | |
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|:------|:--------------------------| |
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| GK | Geekonomy | |
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| OH | Osim History | |
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| DK | The Dor Kahn Experience | |
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| YO | Yo! The podcast | |
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| GQ | Good Question | |
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| YV | Yad vashem | |
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### Data Fields |
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The data have several fields: |
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- `fname`: file name |
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- `audio`: |
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- `array`: array of audio samples |
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- `sample_rate`: audio sampling rate |
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- `path`: path to the audio file saved location |
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- `is_raw`: Flag for raw/preprocessed |
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- `raw`: |
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- `fname`: origin raw file name |
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- `start_sec`: start time mark in seconds |
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- `end_sec`: end time mark in seconds |
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- `source`: Source name |
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- `n_samples`: Number of samples |
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- `text`: Transcription |
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- `normalized_text`: Normalized transcription (details in paper) |
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- `score`: Transcription quality score obtained by forced aligner (details in paper) |
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### Licensing Information |
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Data is licensed under the terms of the Creative Commons Attribution 4.0 |
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International License (CC BY 4.0), The full text of the CC-BY 4.0 license is available at |
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https://creativecommons.org/licenses/by/4.0/. |
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### Acknowledgements |
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This research work was supported by the Israel Innovation Authority, grant number 78563. |
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