Datasets:
Tasks:
Automatic Speech Recognition
Formats:
parquet
Languages:
Xhosa
Size:
1K - 10K
Tags:
low resource languages
License:
File size: 1,996 Bytes
96a0b0e b378525 96a0b0e b378525 8cf3770 96a0b0e b378525 8cf3770 b378525 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 |
---
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: transcription
dtype: string
- name: duration
dtype: float64
splits:
- name: train
num_bytes: 4531568161.596
num_examples: 5154
- name: validation
num_bytes: 1294272351.875
num_examples: 1473
- name: test
num_bytes: 644375190
num_examples: 737
download_size: 6400544345
dataset_size: 6470215703.471
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
license: cc-by-3.0
language:
- xh
task_categories:
- automatic-speech-recognition
tags:
- low resource languages
---
# Xhosa Merged Audio
This dataset was cultivated from [Beijuka/xhosa_parakeet_50hr](https://huggingface.co/datasets/Beijuka/xhosa_parakeet_50hr). This dataset orginally came from NCHLT isiXhosa Speech Corpus (see below).
The original corpus contained audio and transcription in 3-5 word segments. This meant that the majority of the dataset was ~5 seconds long. Whisper can receive an input of 30 seconds. This meant that the dataset required substantial padding. To reduce the amount of padding, the audio segments were merged together sequentially until a limit of 30 seconds was reached.
## Original Dataset
- Name: NCHLT isiXhosa Speech Corpus
- Size: Approximately 56 hours of transcribed speech
- Speakers: 209 (106 female, 103 male)
- Content: Prompted speech (3-5 word utterances read from a smartphone screen)
- Source: Audio recordings smartphone-collected in non-studio environment
- License: Creative Commons Attribution 3.0 Unported License (CC BY 3.0)
### Citation
```tex
De Vries, N.J., Davel, M.H., Badenhorst, J., Basson, W.D., de Wet, F., Barnard, E. and de Waal, A. (2014). A smartphone-based ASR data collection tool for under-resourced languages. Speech Communication, 56, 119-131. https://hdl.handle.net/20.500.12185/279
``` |