datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
uk-text-normalization
Український TTS-нормалізатор — датасет
Пари «письмовий текст → як його вимовляють» для української. Числа, дати, час,
гроші, одиниці, скорочення, коди, телефони, IBAN, домени, пошта, римські
цифри, латинські вкраплення — те, що треба розгорнути словами перед синтезом
мовлення.
{"task_id": 0,
"combo_names": ["Кількісні числівники (написані цифрами)",
"Порядкові числівники (написані цифрами з закінченням)"],
"original": "На 1-й полиці стоять 4 книги."… See the full description on the dataset page: https://huggingface.co/datasets/skypro1111/uk-text-normalization.kyrgyz-text-normalization
Kyrgyz Text Normalization Dataset
A dataset for training and evaluating Kyrgyz text normalization systems. Released subset accompanying "Kyrgyz Text Normalization: A Comparative Study of Neural and Rule-Based Approaches" (MeLLM Workshop @ ACL 2026).
What is in this release
This is a representative 20,000-pair subset of a larger 1.67M-pair training corpus, plus the full 1,000-example human-verified test set used in the paper.
Split
Examples
Source
Verification… See the full description on the dataset page: https://huggingface.co/datasets/Zarinaaa/kyrgyz-text-normalization.turkish-text-normalization
🇹🇷 Turkish Text Normalization (TN / ITN)
A deterministic, rule-based dataset of Turkish written ↔ spoken pairs for
Text Normalization (TN) and Inverse Text Normalization (ITN) — mapping digit/symbol
forms (1.500 TL, %25, 15.07.2026) to their fully spoken Turkish words
(bin beş yüz lira, yüzde yirmi beş, on beş temmuz iki bin yirmi altı) and back.
This is a common, high-value preprocessing step for Turkish ASR post-processing and
TTS front-ends, where numbers, dates, currencies… See the full description on the dataset page: https://huggingface.co/datasets/yagmurtuncer/turkish-text-normalization.turkish-text-normalization-1m
Turkish Text Normalization 1M v2
Kontrollü altı gürültü türüyle Türkçe metin normalizasyon çiftleri.
Doğrulanmış boyut
Train: 980,000
Validation: 10,000
Test: 10,000
Toplam: 1,000,000
Ana görev sütunları: id, noisy_text, normalized_text, noise_type
Provenance
Veri insan mesajlarından, belgelerinden veya web kazımasından alınmamıştır. Tamamı
depodaki üretici koduyla deterministik olarak oluşturulur. Her satırda source_type,
provenance… See the full description on the dataset page: https://huggingface.co/datasets/GoktugD/turkish-text-normalization-1m.Text_Normalization_Challenge_Unittests_Eng_Frabm-text-normalization
bm-text-normalization
Bambara (Bamanankan) orthographic normalisation: map a non-standard spelling to its
standard form. 4,877 short phrase-level pairs in a single config, bamadaba.
Load
from datasets import load_dataset
train = load_dataset("djelia/bm-text-normalization", "bamadaba", split="train")
dev = load_dataset("djelia/bm-text-normalization", "bamadaba", split="dev")
test = load_dataset("djelia/bm-text-normalization", "bamadaba", split="test")
# rows… See the full description on the dataset page: https://huggingface.co/datasets/djelia/bm-text-normalization.text-normalization-benchmark
text-normalization-benchmark
The raw Argilla 2.8.0 export of a Bambara
(Bamanankan) text-normalization project: 160 records from four in-house corpora, each with
the annotator's standard-orthography rewrite. 96 carry a submitted response; 64 were
discarded. For a ready-to-score evaluation set, use
djelia/bm-text-normalization-benchmark, the cleaned export of the 96 finished annotations.
The repo is gated: request access on the Hub and run hf auth login.
Load
from… See the full description on the dataset page: https://huggingface.co/datasets/djelia/text-normalization-benchmark.ml_ta_text_normalizationtamil_ml_text_normalizationbm-text-normalization-benchmark
bm-text-normalization-benchmark
A small human-annotated evaluation set for Bambara (Bamanankan) orthographic normalisation:
96 real-world Bambara strings, each paired with a hand-written standard-orthography rewrite.
It is the cleaned export of the finished annotations from
djelia/text-normalization-benchmark.
Load
from datasets import load_dataset
# the current, whitespace-clean evaluation set
bench = load_dataset("djelia/bm-text-normalization-benchmark"… See the full description on the dataset page: https://huggingface.co/datasets/djelia/bm-text-normalization-benchmark.ta_ml_text_normalizationInverse_Text_Normalization_SinhalaText-Normalization-Hindi