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.asr_inverse_text_normalizationturkish-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-HindiText_Normalization_HindiThe dataset is aimed to train model to take a sentence in Hindi language and normalize
specific entities, including:
Dates (any format)
Currencies
Scientific units
Hindi
input
output
१९८४ में इंदिरा गांधी की हत्या के बाद उनके बेटे राजीव गांधी कॉंग्रेस के नेता और प्रधानमंत्री बने
निन्टीन इटी फोर में इंदिरा गांधी की हत्या के बाद उनके बेटे राजीव गांधी कॉंग्रेस के नेता और प्रधानमंत्री बने
प्रथम स्थाई बस्तियों ने 9000 वर्ष पूर्व स्वरुप लिया था
प्रथम स्थाई बस्तियों ने नाइन थाउजंड वर्ष… See the full description on the dataset page: https://huggingface.co/datasets/KGSAGAR/Text_Normalization_Hindi.