QuranTTS v4

An ear-verified Quranic recitation corpus for TTS and speech restoration.

v4 supersedes the earlier v1_chunks / v2_clean / v2_raw configurations. It is a full re-cut of the corpus at 24-bit / 48 kHz, with ayah boundaries taken from forced alignment rather than fixed padding — which fixes the truncated ghunnah endings present in earlier releases.

Clips	64,721
Duration	301.4 h
Reciters	16
Riwaya / style	Hafs, murattal
Coverage	112 surahs, 6,120 unique ayat
Masters	48 kHz, 24-bit FLAC (data/)
Training copies	24 kHz mono FLAC (v3_24k/)
Mean clip	16.8 s

Layout

metadata.jsonl        one row per clip (see fields below)
data/<reciter>/*.flac 48 kHz 24-bit masters
v3_24k/<reciter>/*.flac  24 kHz mono training copies (same filenames)

from huggingface_hub import snapshot_download

# metadata only
from datasets import load_dataset
meta = load_dataset("Quran-Lab/QuranTTS", split="train")

# full corpus (masters + 24 kHz copies) — ~150 GB
snapshot_download("Quran-Lab/QuranTTS", repo_type="dataset", local_dir="QuranTTS")

# just the 24 kHz training copies — ~56 GB
snapshot_download("Quran-Lab/QuranTTS", repo_type="dataset",
                  allow_patterns=["v3_24k/**", "metadata.jsonl"], local_dir="QuranTTS")

Fields

field	meaning
file_name	path to the 48 kHz master, repo-relative
source_id, reciter, riwaya, style	provenance of the recitation
surah, ayah	canonical ayah reference
text_uthmani, text_imlaei	ayah text in both orthographies
phoneme_tokens	tajweed phoneme sequence (see below)
n_tokens	length of phoneme_tokens
duration_s, sample_rate, bit_depth	audio properties
src_part, src_start_s, src_end_s	exact span in the source recitation
boundary	how the clip end was determined (see below)
align_score, recut_match	alignment confidence, re-cut correlation

Tajweed phonemes

phoneme_tokens uses a tajweed-aware inventory in which elongation length is part of the token: a two-harakat madd is ا:2 and a six-harakat madd is ا:6, qalqalah is marked (بڇ), and shadda/tanwin are carried on the token. A model trained on these tokens learns tajweed duration categorically from the text, without a separate duration model.

Boundaries

Clip ends come from the aligner, not fixed padding:

kind	n	meaning
next_onset	60,928	ends at the onset of the following ayah
pulled_back	1,244	next onset preceded the nominal end; pulled back
pause	2,280	span-final; ends in a verified (quiet and unvoiced) pause
cap	269	hit the maximum extension

This is what preserves ghunnah and madd that run to the very end of an ayah.

Cleaning

Sources were ear-verified before bulk processing, then run through a fixed chain: hum removal → dialogue isolation → dereverberation → denoise → 80 Hz high-pass → 48 kHz → −1 dBFS. Every source was gated on a listening check; reciters that failed were dropped rather than repaired.

Known issues (qc_flags.jsonl)

Each clip's tajweed tokens imply an expected length, so duration / expected gives a per-clip speaking rate. Clips whose rate is >=2x (or <=0.5x) their own reciter's median disagree with their text — they contain extra audio (an isti'adha before the basmala, a trailing ayah, a long silence) or are clipped.

244 clips (0.38%) are flagged this way and listed in qc_flags.jsonl (file_name, rate_ratio, issue). First ayat are affected ~7x more often (2.2% of ayah==1 vs 0.3% of the rest), which is the isti'adha signature. Total excess audio is ~0.7 h. To train on the clean 99.6%:

import json
flag = {json.loads(l)["file_name"] for l in open("qc_flags.jsonl", encoding="utf-8")}
rows = [json.loads(l) for l in open("metadata.jsonl", encoding="utf-8")
        if json.loads(l)["file_name"] not in flag]

Caveats

• Clip durations run long (mean 16.8 s, max 229.8 s). Models with a fixed input ceiling — F5/MAGIC-style TTS caps at 15 s — will need to filter or sub-segment; roughly 43 % of clips exceed 15 s.
• phoneme_tokens are canonical prescriptions derived from the text, not measurements of the audio. Free-choice madd (munfasil, ʿāriḍ) has no single correct value, so token length and realized duration can legitimately differ.
• Hafs murattal only.

License

NPL-1.1 (see LICENSE). The recitations are of the Qur'an; please handle the audio and text with the respect the source warrants.