Datasetpublic

zhaochenyang20/sglang-omni-arabic-tts-smoke

SGLang Omni Arabic TTS Smoke Set This dataset is a fixed 50-sentence Arabic target-text subset derived from the Google FLEURS ar_eg test split. It is intended for lightweight, ASR-based intelligibility checks when integrating Arabic TTS models into SGLang Omni. It is not a standard Arabic TTS benchmark and does not measure naturalness, prosody, speaker similarity, or human preference. Source Dataset: google/fleurs Config: ar_eg Split: test Source revision:… See the full description on the dataset page: https://huggingface.co/datasets/zhaochenyang20/sglang-omni-arabic-tts-smoke.

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Dataset Card

SGLang Omni Arabic TTS Smoke Set

This dataset is a fixed 50-sentence Arabic target-text subset derived from the Google FLEURS ar_eg test split. It is intended for lightweight, ASR-based intelligibility checks when integrating Arabic TTS models into SGLang Omni.

It is not a standard Arabic TTS benchmark and does not measure naturalness, prosody, speaker similarity, or human preference.

Source

—Dataset: google/fleurs
—Config: ar_eg
—Split: test
—Source revision: ab93cf03f9d0cd083c853fad065a6377067408aa
—Source file: ar_eg/test-00000-of-00001.parquet
—License: CC BY 4.0

Selection

Rows are scanned in source order and retained when:

—the transcription contains 6-20 whitespace-delimited words;
—at least 90% of alphabetic characters are Arabic;
—the text contains no digits;
—the normalized whitespace form has not already appeared.

The first 50 matching rows are stored. Digit-containing rows are excluded because ASR may verbalize digits while the written reference retains numeric characters.

Schema

Field	Type	Description
`sample_id`	string	Stable ID derived from the source row index
`target_text`	string	Arabic TTS target text
`word_count`	int64	Whitespace-delimited word count
`source_row_index`	int64	Row index in the pinned FLEURS Parquet file
`source_id`	string	Original FLEURS row ID

The dataset contains text and provenance only. Reference audio and generated model outputs are intentionally not included.

Reproduction

The materialization code lives in SGLang Omni:

bash

python -m benchmarks.audar_tts.prepare_fleurs_dataset \
  --output-dir /tmp/sglang-omni-arabic-tts-smoke \
  --samples 50

manifest.json records the source revision, selection contract, output path, and Parquet SHA-256.

Evaluation

The initial SGLang Omni Audar-TTS smoke run synthesizes these targets with a pinned official Audar reference, transcribes each generated WAV directly to Arabic with Qwen3-ASR-1.7B, and computes WER, CER, BLEU, and chrF++ without translation.