Datasets:
Tasks:
Automatic Speech Recognition
Formats:
webdataset
Languages:
Uzbek
Size:
10K - 100K
Tags:
audio
License:
File size: 1,236 Bytes
93bc619 ebc6d6b c8d1da9 ebc6d6b c8d1da9 ebc6d6b c8d1da9 767c5cb ce07f07 4855b8a ce07f07 4855b8a ce07f07 767c5cb 8c33e03 ce07f07 4855b8a ce07f07 767c5cb |
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 |
---
license: apache-2.0
task_categories:
- automatic-speech-recognition
language:
- uz
pretty_name: Uzbek Language Speech-to-Text Dataset
size_categories:
- 100K<n<1M
---
Dataset Summary
Languages: Uzbek
Size: Varied across different subsets.
Total Audio Duration: Varied
File Formats: .wav and mp3 for audio files, .tsv for transcriptions.
Dataset Structure
The dataset is organized into the following directories and files:
audio/
other/: Contains .tar archives like uz_other_0.taruz_other_1.tar
train/: Contains .tar archives like uz_train_0.tar.
validated/: Contains .tar archives like uz_validated_0.tar, uz_validated_1.tar, and uz_validated_2.tar.
test/: Contains individual .wav files.
transcription/: Contains .tsv files including:
other.tsv
train.tsv
validated.tsv
test.tsv
The .tsv files have two columns: file_name and transcription. Each entry provides the path to the audio file and its corresponding transcription.
Data Instances
A typical data point includes:
Audio File: Path to the .wav and mp3 files.
Transcription: Text transcribed from the audio.
Example data instance:
{
"file_name": "audio/train/common_voice_uz_28907218.mp3",
"transcription": "Bugun ertalab Gyotenikiga taklifnoma oldim."
}
|