programindz/kashmiri-tts-single-speaker
Kashmiri Single Speaker TTS Corpus Overview This repository provides a single-speaker Kashmiri Text-to-Speech (TTS) corpus in Perso-Arabic script. The dataset consists of paired speech recordings and text transcriptions intended for training and evaluating neural text-to-speech systems. All recordings were produced by a single male native Kashmiri speaker. Dataset Statistics Property Value Number of utterances 2984 Total duration 4.42… See the full description on the dataset page: https://huggingface.co/datasets/programindz/kashmiri-tts-single-speaker.
Kashmiri Single Speaker TTS Corpus
Overview
This repository provides a single-speaker Kashmiri Text-to-Speech (TTS) corpus in Perso-Arabic script. The dataset consists of paired speech recordings and text transcriptions intended for training and evaluating neural text-to-speech systems. All recordings were produced by a single male native Kashmiri speaker.
Dataset Statistics
Example
Intended Uses
This dataset is intended for
- Neural Text-to-Speech
- Voice Cloning
- Speech Representation Learning
- Alignment Models
- Pronunciation Modeling
- Low-resource speech research
Source Dataset
This Hugging Face dataset is a structured redistribution of the publicly available KTTS Single Speaker Dataset. The original dataset contains 2,984 single-speaker Kashmiri recordings sampled at 48 kHz together with aligned text transcriptions. It was created to support the development of Kashmiri text-to-speech systems and was recorded using a single male speaker after text collection and quality filtering.
Original source:
https://data.mendeley.com/datasets/5c4dcvxdmb/2
Contributors:
- Kh Mohmad Shafi
- Asif Ali Bhat
- Kamran Imtiyaz
- Javaid Iqbal
Institution:
University of Kashmir
License
Please follow the license of the original dataset.
CC BY-NC 3.0
Citation
If you use this dataset, please cite the original publication.
@dataset{KTTS2024,
author = {Shafi, Kh Mohmad and Bhat, Asif Ali and Imtiyaz, Kamran and Iqbal, Javaid},
title = {KTTS Single Speaker Dataset},
year = {2024},
publisher = {Mendeley Data},
version = {2},
doi = {10.17632/5c4dcvxdmb.2}
}