Datasets:
file name
string | transcript
string | duration
float64 | match quality
string | hypothesis
string | CER
float64 | search type
int64 | ASRs
string | audio
sequence | samplerate
float64 |
---|---|---|---|---|---|---|---|---|---|
302-27.wav | وقتی یک فرد با دوربین دوچشمی | 2.477982 | HIGH | وقتی یک فرد با دوربین دو چشمی | 0.035714 | 1 | ['Wav2Vec'] | [-0.00067138671875,-0.000152587890625,0.000335693359375,0.000885009765625,0.001434326171875,0.001708(...TRUNCATED) | 44,100 |
302-72.wav | علاوهبر این، تلسکوپهای بیوپتیک | 2.413991 | MIDDLE | علاوه بر این تلسکپهای بیوپتیک | 0.0625 | 1 | ['Wav2Vec'] | [0.000457763671875,0.001251220703125,0.001861572265625,0.002227783203125,0.002105712890625,0.0015258(...TRUNCATED) | 44,100 |
125-41.wav | "که بهگفته وزیر تعاون، کار و رفاه اجتماعی، هر پنج معیا(...TRUNCATED) | 7.84 | HIGH | "که به گفته وزیر تعاون کار و رفاح اجتماعی هر پنج معیار ا(...TRUNCATED) | 0.012821 | 1 | ['Wav2Vec'] | [0.030609130859375,0.03448486328125,0.03106689453125,0.02117919921875,0.010223388671875,0.0029602050(...TRUNCATED) | 44,100 |
131-1.wav | ابوذر سمیعی: دکتری سیاستگزاری فرهنگی | 4.46898 | MIDDLE | عبووسر سمیعی دکتری سیاست گذاری فرهنگی | 0.111111 | 1 | ['Wav2Vec'] | [0.003753662109375,0.00091552734375,-0.002227783203125,-0.0042724609375,-0.004791259765625,-0.004180(...TRUNCATED) | 44,100 |
131-48.wav | بهویژه اگر چنین امری در کوتاهمدت محقق شود | 4.103991 | HIGH | به ویژه اگر چنین امری در کوتاه مدت محقق شود | 0 | 1 | ['Wav2Vec'] | [0.00018310546875,0.000579833984375,0.00091552734375,0.00091552734375,0.0006103515625,0.000305175781(...TRUNCATED) | 44,100 |
280-7.wav | پس از دو جنگ جهانی اول و دوم، | 2.532993 | HIGH | پس از دو جنگ جهانی اول و دوم | 0 | 1 | ['Wav2Vec'] | [0.00018310546875,0.000091552734375,0.00006103515625,0.0001220703125,0.0003662109375,0.0006103515625(...TRUNCATED) | 44,100 |
241-53.wav | "و حتی تولید نمونههای مشابه خارجی در داخل کشور، هنوز ا(...TRUNCATED) | 10.62 | HIGH | "و حتی تولید نمونههای مشابه خارجی در داخل کشور هنوز از(...TRUNCATED) | 0.05 | 1 | ['Wav2Vec'] | [0.002685546875,0.002777099609375,0.002899169921875,0.00286865234375,0.002593994140625,0.00234985351(...TRUNCATED) | 44,100 |
241-58.wav | "و این دانشآموز یا از امکان داشتن معلم ویژه یا رابط مح(...TRUNCATED) | 5.094989 | HIGH | "و این دانش آموزیا از امکان داشتن معلم ویژه یا رابط محرو(...TRUNCATED) | 0.016393 | 1 | ['Wav2Vec'] | [0.00030517578125,0.000457763671875,0.000274658203125,0.000244140625,0.00054931640625,0.000610351562(...TRUNCATED) | 44,100 |
241-70.wav | با افرادی مواجه هستیم که نوشتههایشان خوانا نیست. | 3.436984 | HIGH | با افرادی مواجه هستیم که نوشتههایشان خانه نیست | 0.041667 | 1 | ['Wav2Vec'] | [0.000152587890625,0.00018310546875,0.00018310546875,0.000030517578125,-0.000152587890625,-0.0001831(...TRUNCATED) | 44,100 |
461-41.wav | در یک کوچه بنبست متوقف میشود. | 2.860998 | MIDDLE | که در یک کوچه وم بست متوقف میشود | 0.2 | 1 | ['Wav2Vec'] | [0.0018310546875,0.001373291015625,0.000732421875,0.000274658203125,0.000091552734375,-0.00003051757(...TRUNCATED) | 44,100 |
ManaTTS Persian: a recipe for creating TTS datasets for lower resource languages
Mana-TTS is a comprehensive and large-scale Persian Text-to-Speech (TTS) dataset designed for speech synthesis and other speech-related tasks. The dataset has been carefully collected, processed, and annotated to ensure high-quality data for training TTS models. For details on data processing pipeline and statistics, please refer to the paper in the Citation secition.
Acknowledgement
The raw audio and text files have been collected from the archive of Nasl-e-Mana magazine devoted to the blind. We thank the Nasl-e-Mana magazine for their invaluable work and for being so generous with the published dataset license. We also extend our gratitude to the Iran Blind Non-governmental Organization for their support and guidance regarding the need for open access initiatives in this domain.
Data Columns
Each Parquet file contains the following columns:
- file name (
string
): The unique identifier of the audio file. - transcript (
string
): The ground-truth transcript corresponding to the audio. - duration (
float64
): Duration of the audio file in seconds. - match quality (
string
): Either "HIGH" forCER < 0.05
or "MIDDLE" for0.05 < CER < 0.2
between actual and hypothesis transcript. - hypothesis (
string
): The best transcript generated by ASR as hypothesis to find the matching ground-truth transcript. - CER (
float64
): The Character Error Rate (CER) of the ground-truth and hypothesis transcripts. - search type (
int64
): Either 1 indicating the GT transcripts is result of Interval Search or 2 if a result of Gapped Search (refer to paper for more details). - ASRs (
string
): The Automatic Speech Recognition (ASR) systems used in order to find a satisfying matching transcript. - audio (
sequence
): The actual audio data. - samplerate (
float64
): The sample rate of the audio.
Usage
To use the dataset, you can load it directly using the Hugging Face datasets library:
from datasets import load_dataset
dataset = load_dataset("MahtaFetrat/Mana-TTS", split='train')
You can also download specific parts or the entire dataset:
# Download a specific part
wget https://huggingface.co/datasets/MahtaFetrat/Mana-TTS/resolve/main/dataset/dataset_part_01.parquet
# Download the entire dataset
git clone https://huggingface.co/datasets/MahtaFetrat/Mana-TTS
Citation
If you use Mana-TTS in your research or projects, please cite the following paper:
@article{fetrat2024manatts,
title={ManaTTS Persian: a recipe for creating TTS datasets for lower resource languages},
author={Mahta Fetrat Qharabagh and Zahra Dehghanian and Hamid R. Rabiee},
journal={arXiv preprint arXiv:2409.07259},
year={2024},
}
License
This dataset is available under the cc0-1.0. However, the dataset should not be utilized for replicating or imitating the speaker’s voice for malicious purposes or unethical activities, including voice cloning for malicious intent.
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