README.md

---
dataset_info:
  features:
  - name: file_name
    dtype: string
  - name: sentence
    dtype: string
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: duration
    dtype: float64
  - name: sample_rate
    dtype: int64
  - name: __index_level_0__
    dtype: int64
  splits:
  - name: train
    num_bytes: 1226816698.725
    num_examples: 2387
  - name: test
    num_bytes: 301524570.0
    num_examples: 597
  download_size: 1418295955
  dataset_size: 1528341268.725
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
---








### 📌 **Citation for KTTS Single Speaker Dataset**  

#### **KTTS Single Speaker Dataset**  
📅 **Published:** 30 August 2024  
📌 **Version:** 2  
🔗 **DOI:** [10.17632/5c4dcvxdmb.2](https://data.mendeley.com/datasets/5c4dcvxdmb/2)  
👨‍💻 **Contributors:**  
- **Kh Mohmad Shafi**  
- **Asif Ali Bhat**  
- **Kamran Imtiyaz**  
- **Javaid Iqbal**  

🗂 **Original Dataset Link:** [Mendeley Data-KTTS Single Speaker Dataset](https://data.mendeley.com/datasets/5c4dcvxdmb/2)  

---

### 🔹 **Enhanced & Cleaned Version**  
🔖 **Omarrran/kashmiri_single_speaker_tts_hf_dataset_2024** is a **cleaned, structured, and enhanced version** of the original **KTTS Single Speaker Dataset**, modified for **better accessibility and improved usability** in **Text-to-Speech (TTS) training**.  

📌 **Improvements include:**  
✔ **Strict audio-text alignment**  
✔ **Corrected formatting issues**  
✔ **Better dataset structure for machine learning applications**  

🚀 **This version ensures improved reach and ease of use for researchers and developers working on Kashmiri TTS models.**

Description
This dataset has been primarily developed to facilitate the creation of text-to-speech systems for the Kashmiri language, a digitally underrepresented language predominantly spoken in the Jammu and Kashmir region of India. The dataset comprises 2,984 audio recordings in WAV format, each accompanied by its corresponding textual data in a separate file named ‘textcorpus.csv’. The ‘id’ column in the CSV file serves as a unique identifier, allowing users to efficiently locate the corresponding WAV files, which are systematically named according to the ‘id’ associated with the sentences they contain.
All recordings feature a single male voice with a sample rate of 48,000 Hz, ensuring high-quality audio suitable for detailed phonetic analysis and machine learning applications. This consistent audio quality across the dataset provides a reliable foundation for training and testing text-to-speech models. Furthermore, the dataset can be a valuable resource for future research and development efforts aimed at enhancing digital accessibility for the Kashmiri-speaking population. 



# Omarrran/kashmiri_single_speaker_ttd_hf_dataset_2024

## Dataset Description

This dataset contains Kashmiri text-to-speech (TTS) data, including paired text and audio files.

## Dataset Statistics

- Total number of samples: 2984
- Number of samples in train split: 2387
- Number of samples in test split: 597

### Audio Statistics

- Total audio duration: 15914.16 seconds (4.42 hours)
- Average audio duration: 5.33 seconds
- Minimum audio duration: 1.98 seconds
- Maximum audio duration: 12.60 seconds

### Text Statistics

- Total number of words: 31365
- Average number of words per sample: 10.51
- Minimum number of words in a sample: 5
- Maximum number of words in a sample: 26

## Dataset Structure

The dataset contains the following fields:

- `file_name`: Value(dtype='string', id=None)
- `sentence`: Value(dtype='string', id=None)
- `audio`: Audio(sampling_rate=16000, mono=True, decode=True, id=None)
- `duration`: Value(dtype='float64', id=None)
- `sample_rate`: Value(dtype='int64', id=None)
- `__index_level_0__`: Value(dtype='int64', id=None)

## Usage Example

Here's a simple example of how to load and use this dataset:

```python
from datasets import load_dataset

dataset = load_dataset('Omarrran/kashmiri_single_speaker_ttd_hf_dataset_2024')

# Access the training split
train_data = dataset['train']

# Get the first sample
first_sample = train_data[0]
print(f"Text: {first_sample['text']}")
print(f"Audio file: {first_sample['audio']}")
```

## License

Please refer to the dataset card for license information.

## Citation

If you use this dataset in your research, please cite it as follows:

```
@dataset{KTTS Single Speaker Dataset,
  author = {Shafi, Kh Mohmad; Bhat, Asif Ali; Imtiyaz, Kamran ; Iqbal, Javaid (2024), “KTTS Single Speaker Dataset”, Mendeley Data, V2, doi: 10.17632/5c4dcvxdmb.2
},
  title = {Omarrran/kashmiri_single_speaker_ttd_hf_dataset_2024},
  year = {2025},
  url = {https://huggingface.co/datasets/Omarrran/kashmiri_single_speaker_ttd_hf_dataset_2024}
  doi = {10.17632/5c4dcvxdmb.2 },
}
```