| --- |
| 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-description) |
| - [Dataset Summary](#dataset-summary) |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| - [Languages](#languages) |
| - [Dataset Structure](#dataset-structure) |
| - [Data Instances](#data-instances) |
| - [Data Fields](#data-fields) |
| - [Data Splits](#data-splits) |
| - [Dataset Creation](#dataset-creation) |
| - [Curation Rationale](#curation-rationale) |
| - [Source Data](#source-data) |
| - [Annotations](#annotations) |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| - [Considerations for Using the Data](#considerations-for-using-the-data) |
| - [Social Impact of Dataset](#social-impact-of-dataset) |
| - [Discussion of Biases](#discussion-of-biases) |
| - [Other Known Limitations](#other-known-limitations) |
| - [Additional Information](#additional-information) |
| - [Dataset Curators](#dataset-curators) |
| - [Licensing Information](#licensing-information) |
| - [Citation Information](#citation-information) |
| - [Contributions](#contributions) |
|
|
| ## Dataset Description |
|
|
| - **Homepage:** [Tarteel AI](https://www.tarteel.ai/) |
| - **Repository:** [Needs More Information] |
| - **Point of Contact:** [Mohamed Saad Ibn Seddik](mailto:ms.ibnseddik@tarteel.ai) |
|
|
| ### Dataset Summary |
|
|
| This dataset is a collection of Quranic verses and their transcriptions, with diacritization, by different reciters. |
|
|
| ### How to download |
| ``` |
| !pip install -q datasets |
| |
| from datasets import load_dataset |
| dataset =load_dataset("Salama1429/tarteel-ai-everyayah-Quran", verification_mode="no_checks") |
| |
| ``` |
|
|
| ### Supported Tasks and Leaderboards |
|
|
| [Needs More Information] |
|
|
| ### Languages |
|
|
| The audio is in Arabic. |
|
|
| ## Dataset Structure |
|
|
| ### Data Instances |
|
|
| A typical data point comprises the audio file `audio`, and its transcription called `text`. |
| The `duration` is in seconds, and the author is `reciter`. |
|
|
| An example from the dataset is: |
| ``` |
| { |
| 'audio': { |
| 'path': None, |
| 'array': array([ 0. , 0. , 0. , ..., -0.00057983, |
| -0.00085449, -0.00061035]), |
| 'sampling_rate': 16000 |
| }, |
| 'duration': 6.478375, |
| 'text': 'بِسْمِ اللَّهِ الرَّحْمَنِ الرَّحِيمِ', |
| 'reciter': 'abdulsamad' |
| } |
| ``` |
|
|
| ### Length: |
|
|
| Training: |
| Total duration: 2985111.2642479446 seconds |
| Total duration: 49751.85440413241 minutes |
| Total duration: 829.1975734022068 hours |
|
|
| Validation: |
| Total duration: 372720.43139099434 seconds |
| Total duration: 6212.007189849905 minutes |
| Total duration: 103.5334531641651 hours |
|
|
| Test: |
| Total duration: 375509.96909399604 seconds |
| Total duration: 6258.499484899934 minutes |
| Total duration: 104.30832474833224 hours |
|
|
| ### Data Fields |
|
|
| - 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. |
|
|
| - duration: The duration of the audio file. |
|
|
| - reciter: The reciter of the verses. |
|
|
| ### Data Splits |
|
|
| | | Train | Test | Validation | |
| | ----- | ----- | ---- | ---------- | |
| | dataset | 187785 | 23473 | 23474 | |
|
|
| ### reciters |
| - reciters_count: 36 |
| - reciters: {'abdul_basit', |
| 'abdullah_basfar', |
| 'abdullah_matroud', |
| 'abdulsamad', |
| 'abdurrahmaan_as-sudais', |
| 'abu_bakr_ash-shaatree', |
| 'ahmed_ibn_ali_al_ajamy', |
| 'ahmed_neana', |
| 'akram_alalaqimy', |
| 'alafasy', |
| 'ali_hajjaj_alsuesy', |
| 'aziz_alili', |
| 'fares_abbad', |
| 'ghamadi', |
| 'hani_rifai', |
| 'husary', |
| 'karim_mansoori', |
| 'khaalid_abdullaah_al-qahtaanee', |
| 'khalefa_al_tunaiji', |
| 'maher_al_muaiqly', |
| 'mahmoud_ali_al_banna', |
| 'menshawi', |
| 'minshawi', |
| 'mohammad_al_tablaway', |
| 'muhammad_abdulkareem', |
| 'muhammad_ayyoub', |
| 'muhammad_jibreel', |
| 'muhsin_al_qasim', |
| 'mustafa_ismail', |
| 'nasser_alqatami', |
| 'parhizgar', |
| 'sahl_yassin', |
| 'salaah_abdulrahman_bukhatir', |
| 'saood_ash-shuraym', |
| 'yaser_salamah', |
| 'yasser_ad-dussary'} |
| |
|
|
| ## 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](https://creativecommons.org/licenses/by/4.0/) |
|
|
| ### Citation Information |
|
|
| ``` |
| ``` |
|
|
| ### Contributions |
|
|
| This dataset was created by: |
|
|
