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---
license: cc-by-4.0
size_categories:
- 1M<n<10M
configs:
- config_name: pre
data_files:
- pre/*/*.arrow
- config_name: raw
data_files:
- raw/*/*.arrow
- config_name: GK
data_files:
- pre/geekonomy/*.arrow
- raw/geekonomy/*.arrow
- config_name: GK_pre
data_files: pre/geekonomy/*.arrow
- config_name: GK_raw
data_files: raw/geekonomy/*.arrow
- config_name: OH
data_files:
- pre/osim-history/*.arrow
- raw/osim-history/*.arrow
- config_name: OH_pre
data_files: pre/osim-history/*.arrow
- config_name: OH_raw
data_files: raw/osim-history/*.arrow
- config_name: DK
data_files:
- pre/dor/*.arrow
- raw/dor/*.arrow
- config_name: DK_pre
data_files: pre/dor/*.arrow
- config_name: DK_raw
data_files: raw/dor/*.arrow
- config_name: YO
data_files:
- pre/Yo_the_podcast/*.arrow
- raw/Yo_the_podcast/*.arrow
- config_name: YO_pre
data_files: pre/Yo_the_podcast/*.arrow
- config_name: YO_raw
data_files: raw/Yo_the_podcast/*.arrow
- config_name: YV
data_files:
- pre/Yad_vashem/*.arrow
- raw/Yad_vashem/*.arrow
- config_name: YV_pre
data_files: pre/Yad_vashem/*.arrow
- config_name: YV_raw
data_files: raw/Yad_vashem/*.arrow
---
# HebDB
**Paper:** http://arxiv.org/abs/2407.07566
If you use our datasets, please use the following:
```
@article{turetzky2024hebdb,
title={HebDB: a Weakly Supervised Dataset for Hebrew Speech Processing},
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},
journal={arXiv preprint arXiv:2407.07566},
year={2024}
}
```
### Dataset Summary
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.
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`.
#### How do I download this?
##### Using 🤗 Datasets
```python
from datasets import load_dataset
# pre only
hebdb_pre = load_dataset("SLPRL-HUJI/HebDB", "pre")
# raw only
hebdb_raw = load_dataset("SLPRL-HUJI/HebDB", "raw")
# One specific source(see code list below), both raw and pre
geekonomy = load_dataset("SLPRL-HUJI/HebDB", "GK")
# One specific source, both raw and pre
geekonomy_pre = load_dataset("SLPRL-HUJI/HebDB", "GK_pre")
```
To avoid downloading the entire dataset you can load it in streaming mode using `streaming=True`, for example:
```python
hebdb_pre = load_dataset("SLPRL-HUJI/HebDB", "pre", streaming=True)
```
You can also load and mix:
```python
from datasets import concatenate_datasets, load_dataset
geekonomy = load_dataset("SLPRL-HUJI/HebDB", "GK_pre")
osim_history = load_dataset("SLPRL-HUJI/HebDB", "OH_pre")
# Concatenate both datasets
concatenated = concatenate_datasets([geekonomy, osim_history])
```
### Sources
The 6 available sources are reported in the table below.
| code | name |
|:------|:--------------------------|
| GK | Geekonomy |
| OH | Osim History |
| DK | The Dor Kahn Experience |
| YO | Yo! The podcast |
| GQ | Good Question |
| YV | Yad vashem |
### Data Fields
The data have several fields:
- `fname`: file name
- `audio`:
- `array`: array of audio samples
- `sample_rate`: audio sampling rate
- `path`: path to the audio file saved location
- `is_raw`: Flag for raw/preprocessed
- `raw`:
- `fname`: origin raw file name
- `start_sec`: start time mark in seconds
- `end_sec`: end time mark in seconds
- `source`: Source name
- `n_samples`: Number of samples
- `text`: Transcription
- `normalized_text`: Normalized transcription (details in paper)
- `score`: Transcription quality score obtained by forced aligner (details in paper)
### Licensing Information
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/.
### Acknowledgements
This research work was supported by the Israel Innovation Authority, grant number 78563.
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