| ---
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| language:
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| - tr
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| license: cc-by-4.0
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| task_categories:
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| - text-generation
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| - other
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| tags:
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| - turkish
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| - text-normalization
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| - inverse-text-normalization
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| - itn
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| - tts
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| - asr-post-processing
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| - numbers
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| - dates
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| - synthetic-data
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| - rule-based
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| pretty_name: Turkish Text Normalization (TN/ITN)
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| size_categories:
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| - 10K<n<100K
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| configs:
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| - config_name: default
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| data_files:
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| - split: train
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| path: data/train.csv
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| - split: test
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| path: data/test.csv
|
| ---
|
|
|
| # 🇹🇷 Turkish Text Normalization (TN / ITN)
|
|
|
| A deterministic, **rule-based** dataset of Turkish **written ↔ spoken** pairs for
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| **Text Normalization (TN)** and **Inverse Text Normalization (ITN)** — mapping digit/symbol
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| forms (`1.500 TL`, `%25`, `15.07.2026`) to their fully spoken Turkish words
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| (`bin beş yüz lira`, `yüzde yirmi beş`, `on beş temmuz iki bin yirmi altı`) and back.
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|
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| This is a common, high-value preprocessing step for **Turkish ASR post-processing** and
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| **TTS front-ends**, where numbers, dates, currencies and percentages must be verbalized.
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|
|
| > **Provenance & honesty:** every pair is **generated programmatically** with transparent
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| > linguistic rules (Turkish cardinal/ordinal number grammar, month names, decimal reading
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| > conventions). No text is scraped and no private data is used. The full generator is included
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| > ([`build_dataset.py`](build_dataset.py)) so the dataset is **100% reproducible** from a fixed seed.
|
|
|
| ---
|
|
|
| ## 📦 Contents
|
|
|
| | Split | Rows |
|
| |-------|-----:|
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| | Train | 15,398 |
|
| | Test | 1,711 |
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| | **Total** | **17,109** |
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|
|
| ### Fields
|
|
|
| | Column | Description |
|
| |--------|-------------|
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| | `id` | Row index within the split |
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| | `category` | One of: `cardinal`, `ordinal`, `decimal`, `percentage`, `currency`, `date`, `time` |
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| | `written` | Digit / symbol form (the "written" surface form) |
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| | `spoken` | Fully verbalized Turkish words (lowercase) |
|
|
|
| ### Category distribution (unique pairs)
|
|
|
| | Category | Count | Example (`written` → `spoken`) |
|
| |----------|------:|--------------------------------|
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| | cardinal | 4,259 | `2026` → `iki bin yirmi altı` |
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| | decimal | 3,497 | `530,5` → `beş yüz otuz virgül beş` |
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| | date | 3,082 | `15.07.2026` → `on beş temmuz iki bin yirmi altı` |
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| | currency | 3,051 | `1500 TL` → `bin beş yüz lira` |
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| | ordinal | 1,683 | `523.` → `beş yüz yirmi üçüncü` |
|
| | time | 1,101 | `14:30` → `saat on dört buçuk` |
|
| | percentage | 436 | `%25` → `yüzde yirmi beş` |
|
|
|
| ---
|
|
|
| ## 🚀 Usage
|
|
|
| ```python
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| from datasets import load_dataset
|
|
|
| ds = load_dataset("yagmurtuncer/turkish-text-normalization")
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|
|
| # ITN (spoken -> written) or TN (written -> spoken)
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| ex = ds["train"][0]
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| print(ex["written"], "→", ex["spoken"])
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| ```
|
|
|
| Typical uses:
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| - Train/evaluate a **seq2seq normalizer** (`written` → `spoken` for TTS, or `spoken` → `written` for ASR)
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| - Rule-engine **regression tests** for Turkish verbalization
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| - Data augmentation for Turkish ASR/TTS pipelines
|
|
|
| ---
|
|
|
| ## 🏗️ How it was built (reproducible)
|
|
|
| ```bash
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| python build_dataset.py # regenerates data/ deterministically (seed = 42)
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| python validate.py # 6 data-quality checks, all must pass
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| ```
|
|
|
| The generator implements Turkish number grammar directly:
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| - **Cardinals** up to the billions (`bin` not `bir bin`, `bir milyon`, correct `yüz`/`bin` scaling)
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| - **Ordinals** via a vetted last-word suffix map (`dört` → `dördüncü`, `on` → `onuncu`)
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| - **Dates** with Turkish month names, **times** (incl. `buçuk`), **currency** (TL / $ / € / ₺),
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| **percentages** (`yüzde …`), and **decimals** (`virgül …`)
|
|
|
| ### Conventions
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| - `spoken` is **lowercased Turkish** (letters + spaces only — enforced by `validate.py`)
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| - Decimal fractions with a leading zero are read **digit-by-digit** (`0,05` → `sıfır virgül sıfır beş`);
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| otherwise the fraction is read as a whole number (`3,14` → `üç virgül on dört`)
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| - Pairs are **globally de-duplicated** on `(written, spoken)` — counts reflect *unique* examples,
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| not inflated repetitions
|
|
|
| ---
|
|
|
| ## ✅ Data Quality
|
|
|
| `validate.py` enforces: non-empty fields · valid category set · `spoken` charset ·
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| global `(written, spoken)` uniqueness · all categories present · every `written` contains a digit.
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| All checks pass on the released data.
|
|
|
| ---
|
|
|
| ## ⚠️ Limitations
|
|
|
| - Rule-generated: covers standard verbalizations, not every colloquial reading
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| (e.g. clock time also has `çeyrek geçe` styles not exhaustively included)
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| - Small `percentage` count is intentional — whole percentages only span 0–100, and duplicates
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| are removed rather than padded
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| - Not a substitute for a full production normalizer; intended for training, testing and prototyping
|
|
|
| ---
|
|
|
| ## 📄 License & Citation
|
|
|
| Released under **CC-BY-4.0**.
|
|
|
| ```bibtex
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| @misc{tuncer_turkish_text_normalization,
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| title = {Turkish Text Normalization (TN/ITN)},
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| author = {Nur Yağmur Tuncer},
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| year = {2026},
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| url = {https://huggingface.co/datasets/yagmurtuncer/turkish-text-normalization}
|
| }
|
| ```
|
|
|
