---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 12501351756.72
    num_examples: 14547
  download_size: 11108643698
  dataset_size: 12501351756.72
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: apache-2.0
task_categories:
- automatic-speech-recognition
language:
- uz
tags:
- podcasts
- tashkent
pretty_name: Tashkent dialect focused podcasts youtube uzbek speech
size_categories:
- 10K<n<100K
---


# Tashkent dialect focused podcasts youtube uzbek speech

## Dataset Description

This dataset contains **audio clips and their corresponding transcriptions in the Uzbek language with mostly tashkent dialects**. The data was collected from publicly available podcast videos on YouTube. It is designed for training and evaluating Automatic Speech Recognition (ASR) models.

Most of the content comes from the Jahongir Latipov interviews and Bu podcast (respect authors) YouTube videos. The data was transcribed using Gemini 2.5 Pro and was intelligently filtered.

The audio clips are segmented and formatted for easy use with modern deep learning frameworks.

Support my works and open-source movement: https://tirikchilik.uz/islomovs

## How to Use

You can load the dataset using the 🤗 `datasets` library:

```python
from datasets import load_dataset

# Load the dataset
ds = load_dataset("islomov/podcasts_tashkent_dialect_youtube_uzbek_speech_dataset")

# You can access the 'train' split (default)
train_dataset = ds["train"]

# Print the first example
print(train_dataset[0])
# Expected output:
# {
#   'id': '00001',
#   'audio': {'path': '...', 'array': array([...], dtype=float32), 'sampling_rate': 16000},
#   'text': 'mana shu narsaga hozir javob topishga harakat qilamiz...'
# }
```

## Dataset Structure
Data Fields
- id (string): A unique, zero-padded numeric identifier for each audio sample (e.g., "00001").
- audio (datasets.Audio): An audio object containing the path, raw audio array, and sampling rate. The audio is standardized to a 16kHz sampling rate.
- text (string): The ground truth transcription of the audio clip.

## Data Curation
The audio was sourced from Tashkent dialects and casual speech focused Uzbek-language Podcast YouTube channels. The original videos were downloaded, segmented into smaller clips, and transcribed. The transcriptions in the text column represent the ground truth for ASR tasks.

## Citation
If you use this dataset in your work, please consider citing it:
```
@dataset{islomov_it_youtube_uzbek_speech_dataset,
  author = {Islomov},
  title = {Tashkent dialect focused podcasts youtube uzbek speech},
  year = {2025},
  publisher = {Hugging Face},
  version = {1.0.0},
  url = {https://huggingface.co/datasets/islomov/podcasts_tashkent_dialect_youtube_uzbek_speech_dataset}
}
```

## License
This dataset is licensed under the Apache License 2.0. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.