| --- |
| license: cc-by-nc-sa-4.0 |
| language: |
| - ar |
| task_categories: |
| - automatic-speech-recognition |
| tags: |
| - speaker-diarization |
| - arabic |
| - saudi |
| - sada |
| pretty_name: SADA 2022 Arabic Diarization |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-*.parquet |
| - split: validation |
| path: data/validation-*.parquet |
| - split: test |
| path: data/test-*.parquet |
| - split: preview |
| path: data/preview-*.parquet |
| - split: smoke |
| path: data/smoke-*.parquet |
| - config_name: train-v1 |
| data_files: |
| - split: train |
| path: train-v1/data/*.parquet |
| --- |
| |
|
|
| # SADA 2022 Arabic Diarization |
|
|
| Training-ready speaker-attributed ASR windows derived from |
| [SADA 2022](https://www.kaggle.com/datasets/sdaiancai/sada2022). The source |
| recordings are mirrored at |
| [khaledalganem/sada2022](https://huggingface.co/datasets/khaledalganem/sada2022). |
|
|
| ## Splits |
|
|
| - `train`: 36,004 windows, 202.064 hours, 4,062 recordings |
| - `validation`: 853 windows, 4.774 hours, 88 recordings |
| - `test`: 901 windows, 5.006 hours, 111 recordings |
|
|
| Total: **37,758 windows** and |
| **211.844 hours**. |
|
|
| The official SADA train, validation, and test partitions are preserved. |
| Windows are 8–28 seconds, contain 1–4 locally remapped speakers, and have at |
| least 45% annotated speech. Windows from the same source |
| recording do not materially overlap. Ambiguous speaker labels and overlapping |
| speech annotations are excluded from v1. |
|
|
| Audio is resampled to 16 kHz mono FLAC. Background noise and music are retained; |
| no denoising is applied. |
|
|
| ## Columns |
|
|
| - `audio`: prepared FLAC window |
| - `segments`: speaker, timestamps, transcript, dialect, gender, age, environment |
| - `target`: SyvAI-style speaker/timestamp/text sequence |
| - `source_file`, `source_start`, `source_end`: source provenance |
| - `speaker_count`, `turn_count`, `speech_coverage`, `environment` |
| - `audio_sha256`, `qa_flags`, `review_status`, `license` |
|
|
| ## Target format |
|
|
| ```text |
| <|spltoken0|><|t:0.0|>السلام عليكم<|t:2.1|> |
| ``` |
|
|
| Speaker IDs are local to each window and ordered by first appearance. |
| Timestamp tokens use 100 ms resolution. |
|
|
| ## License and attribution |
|
|
| SADA was created by the Saudi Data and Artificial Intelligence Authority |
| (SDAIA) and the Saudi Broadcasting Authority (SBA). This derivative is |
| released under **CC BY-NC-SA 4.0** and is restricted to non-commercial use. |
|
|
| Changes made: selected timestamped regions, excluded unsupported annotations, |
| remapped speaker IDs locally, resampled audio, encoded FLAC, and generated |
| speaker-attributed sequence targets. |
|
|
| <!-- STEP3C_TRAIN_V1_START --> |
| ## `train-v1`: balanced real + conversational mixtures |
| |
| `train-v1` is a non-commercial Arabic speaker-attributed ASR training |
| configuration derived entirely from SADA2022. It contains **30,000 |
| windows / 164.317 hours**: |
| |
| - 17,727 selected real SADA TRAIN windows (102.061 h) |
| - 12,273 deterministic conversational mixtures (62.256 h) |
| - speaker counts 1/2/3/4: 6,000 / 9,000 / 9,000 / 6,000 |
| - synthetic active-speech overlap: 13.95% |
| - 60 Parquet shards with embedded 16 kHz mono FLAC |
| |
| The official SADA validation and test material is **not included** in this |
| configuration. Source recordings are disjoint from held-out recordings and |
| the final audit found zero held-out ID overlap. |
| |
| ### Fields |
| |
| - `audio`: embedded 16 kHz mono FLAC (`bytes`, `path`) |
| - `text`: Arabic transcript without control tokens |
| - `target`: `<|spltokenK|><|t:start|>text<|t:end|>` sequence; no count token |
| - `segments`: structured local speaker, start/end seconds, and text |
| - `rttm_text`: exact RTTM activity labels |
| - `speaker_count`, overlap statistics/bucket, and pause durations |
| - `real_vs_synthetic`, recipe version, recipe JSON, and source provenance |
| - audio, row, shard, and source checksums |
| - split, attribution, and license metadata |
|
|
| ### Synthetic method and limitations |
|
|
| Mixtures use full annotated Arabic utterances from canonical SADA TRAIN |
| recordings, deterministic seed 30072026, conversational pause sampling, and |
| none/light/medium/heavy overlap buckets. At most two speakers overlap and no |
| utterance is clipped to create an interruption. |
|
|
| SADA speaker labels are file-local. Different source recordings are treated |
| as distinct speaker proxies, but they are not proven to contain different |
| people. The material is Saudi broadcast speech and is not a complete model of |
| all Arabic dialects, channels, or spontaneous conversation. |
|
|
| ### License and attribution |
|
|
| SADA was created by the Saudi Data and Artificial Intelligence Authority |
| (SDAIA) and the Saudi Broadcasting Authority (SBA). This transformation is |
| released under **CC BY-NC-SA 4.0**: non-commercial use only, with attribution |
| and ShareAlike. Cite the original SADA dataset and paper. |
|
|
| Integrity: shard manifest `1f7854d8333e2aa139f0ded6aa56f41d3ecaa3ef4988b7dff40b3e75cb94b3ab`; validation |
| report `28e6c96a4c0bf1d55b946451bb9f70be1f206901d45c77ba7c31f6dd8001a8eb`. |
| <!-- STEP3C_TRAIN_V1_END --> |
| |
