README.md

metadata

pretty_name: Tarteel AI - EveryAyah Dataset
dataset_info:
  features:
    - name: audio
      dtype: audio
    - name: duration
      dtype: float64
    - name: text
      dtype: string
    - name: reciter
      dtype: string
  splits:
    - name: train
      num_bytes: 262627688145.3
      num_examples: 187785
    - name: test
      num_bytes: 25156009734.72
      num_examples: 23473
    - name: validation
      num_bytes: 23426886730.218
      num_examples: 23474
  download_size: 117190597305
  dataset_size: 311210584610.23804
annotations_creators:
  - expert-generated
language_creators:
  - crowdsourced
language:
  - ar
license:
  - mit
multilinguality:
  - monolingual
paperswithcode_id: tarteel-everyayah
size_categories:
  - 100K<n<1M
source_datasets:
  - original
task_categories:
  - automatic-speech-recognition
task_ids: []
train-eval-index:
  - config: clean
    task: automatic-speech-recognition
    task_id: speech_recognition
    splits:
      train_split: train
      eval_split: test
      validation_split: validation
    col_mapping:
      audio: audio
      text: text
      reciter: text
    metrics:
      - type: wer
        name: WER
      - type: cer
        name: CER

Dataset Card for Tarteel AI's EveryAyah Dataset

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: Tarteel AI
• Repository: [Needs More Information]
• Point of Contact: Nawar Halabi

Dataset Summary

This Speech corpus has been developed as part of PhD work carried out by Nawar Halabi at the University of Southampton. The corpus was recorded in south Levantine Arabic (Damascian accent) using a professional studio. Synthesized speech as an output using this corpus has produced a high quality, natural voice.

Supported Tasks and Leaderboards

[Needs More Information]

Languages

The audio is in Arabic.

Dataset Structure

Data Instances

A typical data point comprises the path to the audio file, usually called file and its transcription, called text. An example from the dataset is:

{
    'file': '/Users/username/.cache/huggingface/datasets/downloads/extracted/baebe85e2cb67579f6f88e7117a87888c1ace390f4f14cb6c3e585c517ad9db0/arabic-speech-corpus/wav/ARA NORM  0002.wav',
    'audio': {'path': '/Users/username/.cache/huggingface/datasets/downloads/extracted/baebe85e2cb67579f6f88e7117a87888c1ace390f4f14cb6c3e585c517ad9db0/arabic-speech-corpus/wav/ARA NORM  0002.wav',
               'array': array([-0.00048828, -0.00018311, -0.00137329, ...,  0.00079346, 0.00091553,  0.00085449], dtype=float32),
               'sampling_rate': 48000},
        'orthographic': 'waraj~aHa Alt~aqoriyru Al~a*iy >aEad~ahu maEohadu >aboHaA^i haDabapi Alt~ibiti fiy Alo>akaAdiymiy~api AlS~iyniy~api liloEuluwmi - >ano tasotamir~a darajaAtu AloHaraArapi wamusotawayaAtu Alr~uTuwbapi fiy Alo<irotifaAEi TawaAla ha*aA Aloqarono',
    'phonetic': "sil w a r a' jj A H a tt A q r ii0' r u0 ll a * i0 < a E a' dd a h u0 m a' E h a d u0 < a b H aa' ^ i0 h A D A' b a t i0 tt i1' b t i0 f i0 l < a k aa d ii0 m ii0' y a t i0 SS II0 n ii0' y a t i0 l u0 l E u0 l uu0' m i0 sil < a' n t a s t a m i0' rr a d a r a j aa' t u0 l H a r aa' r a t i0 w a m u0 s t a w a y aa' t u0 rr U0 T UU0' b a t i0 f i0 l Ah i0 r t i0 f aa' E i0 T A' w A l a h aa' * a l q A' r n sil",
    'text': '\ufeffwaraj~aHa Alt~aqoriyru Al~aTHiy >aEad~ahu maEohadu >aboHaA^i haDabapi Alt~ibiti fiy Alo>akaAdiymiy~api AlS~iyniy~api liloEuluwmi - >ano tasotamir~a darajaAtu AloHaraArapi wamusotawayaAtu Alr~uTuwbapi fiy Alo<irotifaAEi TawaAla haTHaA Aloqarono'
}

Data Fields

• file: A path to the downloaded audio file in .wav format.

• audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: dataset[0]["audio"] the audio file is automatically decoded and resampled to dataset.features["audio"].sampling_rate. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the "audio" column, i.e. dataset[0]["audio"] should always be preferred over dataset["audio"][0].

• text: the transcription of the audio file.

• phonetic: the transcription in phonentics format.

• orthographic: the transcriptions written in orthographic format.

Data Splits

	Train	Test	Validation
dataset	187785	23473	23474

Dataset Creation

Curation Rationale

Source Data

Initial Data Collection and Normalization

Who are the source language producers?

Annotations

Annotation process

Who are the annotators?

Personal and Sensitive Information

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[Needs More Information]

Additional Information

Dataset Curators

Licensing Information

CC BY 4.0

Citation Information

Contributions

This dataset was created by: