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README.md
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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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- 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:** https://arxiv.org/abs/???
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If you use our datasets, please use the following:
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```
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@cite{
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Soon
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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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