Datasets:
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---
dataset_info:
features:
- name: uid
dtype: string
- name: file_id
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: sentence
dtype: string
- name: n_segment
dtype: int32
- name: duration_ms
dtype: float32
- name: language
dtype: string
- name: sample_rate
dtype: int32
- name: course
dtype: string
- name: sentence_length
dtype: int32
- name: n_tokens
dtype: int32
splits:
- name: train
num_bytes: 99661277809.752
num_examples: 75924
download_size: 83572532883
dataset_size: 99661277809.752
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- automatic-speech-recognition
language:
- he
size_categories:
- 10K<n<100K
---
## Data Description
Hebrew Speech Recognition dataset from [Campus IL](https://campus.gov.il/).
Data was scraped from the Campus website, which contains video lectures from various courses in Hebrew.
Then subtitles were extracted from the videos and aligned with the audio.
Subtitles that are not on Hebrew were removed (WIP: need to remove non-Hebrew audio as well, e.g. using simple classifier).
Samples with duration less than 3 second were removed.
Total duration of the dataset is 152 hours.
Outliers in terms of the duration/char ratio were not removed, so it's possible to find suspiciously long or short sentences compared to the duration.
Note: dataset is suspiciously huge (probably original files with 22050Hz are in, too). if loading is slow, just clone it :
`git clone hebrew_speech_campus && cd hebrew_speech_campus && git lfs pull`
and load it from the folder `load_dataset("./hebrew_speech_campus")`
## Data Format
Audio files are in WAV format, 16kHz sampling rate, 16bit, mono. Ignore `path` field, use `audio.array` field value.
## Data Usage
```python
from datasets import load_dataset
ds = load_dataset("imvladikon/hebrew_speech_campus", split="train", streaming=True)
print(next(iter(ds)))
```
## Data Sample
```
{'uid': '10c3eda27cf173ab25bde755d0023abed301fcfd',
'file_id': '10c3eda27cf173ab25bde755d0023abed301fcfd_13',
'audio': {'path': '/content/hebrew_speech_campus/data/from_another_angle-_mathematics_teaching_practices/10c3eda27cf173ab25bde755d0023abed301fcfd_13.wav',
'array': array([ 5.54326562e-07, 3.60812592e-05, -2.35188054e-04, ...,
2.34067178e-04, 1.55649337e-04, 6.32447700e-05]),
'sampling_rate': 16000},
'sentence': 'ืืืืืจืื ืฆืจืืืื ืืงืืช ืขืืื ืืืจืืืช, ืืืืืืช ืืืืืืื ืื ืืืืืจ, ืืฉืื ืฆืจืื ืืืืืช ืืืืื',
'n_segment': 13,
'duration_ms': 6607.98193359375,
'language': 'he',
'sample_rate': 16000,
'course': 'from_another_angle-_mathematics_teaching_practices',
'sentence_length': 79,
'n_tokens': 13}
```
## Data Splits and Stats
Split: train
Number of samples: 75924
## Citation
Please cite the following if you use this dataset in your work:
```
@misc{imvladikon2023hebrew_speech_campus,
author = {Gurevich, Vladimir},
title = {Hebrew Speech Recognition Dataset: Campus},
year = {2023},
howpublished = \url{https://huggingface.co/datasets/imvladikon/hebrew_speech_campus},
}
```
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