---
language: eu
tags:
- basque
- euskara
- dialect-identification
- euskalkiak
- azpieuskalkiak
- fasttext
- ahotsak
- zuberera
- suazia
license: mit
datasets:
- xnli-dialectal
- klasikoak
- eitb-parcc
- ahotsak
- suazia-zuberotarra
metrics:
- accuracy
- f1
---

# Zeineuski — Basque Dialect Identification

Fine-grained dialect identification (DID) system for Basque (Euskara). Given a text or speech sample, classifies it into one of six dialect categories: Western (Bizkaiera), Central (Gipuzkera), Navarrese, Navarrese-Labourdin, Souletin (Zuberera), or Standard Basque (Batua).

**Source code:** [github.com/itzune/zeineuski](https://github.com/itzune/zeineuski)

## Architecture

Zeineuski uses a **three-tier hierarchical classification** architecture:

```
Tier 1: batua / dialectal (binary)
  └─ Tier 2: 5-class euskalkia (dialect classification)
       └─ Tier 3: 12-class azpieuskalkia (sub-dialect classification)
```

### Classification taxonomy

The project follows **Koldo Zuazo's dialect classification**, which is the current
linguistic consensus and the basis for Ahotsak.eus's municipality→dialect mapping.

Zuazo recognizes **6 euskalkiak** (dialects):

| # | Euskalkia | Our label | Notes |
|---|-----------|-----------|-------|
| 1 | Bizkaiera / Mendebalekoa | `western` | |
| 2 | Gipuzkera / Erdialdekoa | `central` | |
| 3 | Goi-nafarrera | `navarrese` | Upper Navarrese |
| 4 | Ekialdeko nafarrera / Erronkariera | *(merged into navarrese)* | Extinct ~1990s; tiny data |
| 5 | Zuberera | `souletin` | |
| 6 | Nafar-lapurtera | `nav-lab` | |
| + | Euskara batua | `batua` | Standard unified Basque |

**Why 5 euskalkis + batua instead of 6 + batua?**

Ekialdeko nafarrera (Salazarese/Roncalese) is linguistically a distinct dialect, but
it has been functionally extinct since the 1990s (last native speaker died in 1991).
Ahotsak.eus has only ~65 passages across 7 towns in the Zaraitzu and Erronkari valleys.
The Klasikoak.armiarma.eus classical literature corpus — which provides most of our
Tier-2 training data — maps these texts to `navarrese` since the dialect distinction
is not present in pre-20th-century literary sources.

For **Tier 3 (azpieuskalkia)**, we follow the **Zuazo azpieuskalki taxonomy** as
implemented on [Ahotsak.eus](https://ahotsak.eus). The official Ahotsak municipality→
azpieuskalki mapping provides the ground truth labels for sub-dialect classification.

## Data Sources

| Source | Content | Dialects | Status |
|---|---|---|---|
| [Klasikoak](https://klasikoak.armiarma.eus/) | Literary texts (pre-20th c.) | 5 euskalkis | Train |
| [Ahotsak.eus](https://ahotsak.eus) | Oral history transcriptions | 12 azpieuskalkis | Train + Test |
| [SÜ AZIA](https://web.archive.org/web/20110920103304/http://www.suazia.com) | Pastoral scripts + blog articles | Zuberera | Train + Test |

See [docs/data_sources/suazia_zuberotarra.md](https://github.com/itzune/zeineuski/blob/main/docs/data_sources/suazia_zuberotarra.md) for the SÜ AZIA corpus documentation.

## Models

### Euskalki (Dialect) Classification — 5 euskalkis + batua (6-class)

Hierarchical 2-step classifier (binary batua/dialectal → 5-class euskalkiak):

| Variant | Filename | Size | XNLI (3-class) | Test (4-class) | Batua F1 |
|---------|----------|------|:---:|:---:|:---:|
| final | `hier_binary_final.bin` + `hier_dialect_final.bin` | 1.5GB | 92.42% | 95.18% | 0.962 |
| quantized | `hier_*_quantized.bin` | 417MB | 92.38% | 95.16% | 0.961 |
| compact | `hier_*_compact.bin` | 189MB | 91.78% | 94.71% | 0.957 |
| tiny | `hier_*_tiny.bin` | 112MB | 91.90% | 94.88% | 0.961 |
| **web** | `hier_binary_web.bin` + `hier_dialect_web.bin` | **32MB** | **91.06%** | **94.33%** | **0.952** |

Per-class F1 (final): Western 0.953, Central 0.933, Nav-Lab 0.949, Batua 0.962.

### Azpieuskalki (Sub-Dialect) Classification — 12-class (v2, 2026-06-11)

Fine-grained sub-dialect classifier trained on Ahotsak.eus oral history transcriptions
and augmented with the **SÜ AZIA Zuberotarra corpus** (6,676 pastoral + blog sentences).

**Training data (42,229 sentences):**

| Azpieuskalki | Sentences | % | Source |
|---|---:|---:|---|
| mendebal-sortaldea | 13,059 | 30.9% | Ahotsak |
| erdialde-sartaldea | 9,804 | 23.2% | Ahotsak |
| **zuberera** | **6,050** | **14.3%** | **Ahotsak (441) + SÜ AZIA (6,676)** |
| erdialde-sortaldea | 4,966 | 11.8% | Ahotsak |
| nafar-ipar-sartaldea | 1,966 | 4.7% | Ahotsak |
| nafar-sortaldea | 1,516 | 3.6% | Ahotsak |
| naflap-sortaldea | 1,395 | 3.3% | Ahotsak |
| nafar-hego-sartaldea | 1,101 | 2.6% | Ahotsak |
| naflap-sartaldea | 726 | 1.7% | Ahotsak |
| ekialde-nafarra | 710 | 1.7% | Ahotsak |
| nafar-erdigunea | 497 | 1.2% | Ahotsak |
| mendebal-sartaldea | 439 | 1.0% | Ahotsak |

**Results (84.06% overall on 7,445 test samples):**

| Azpieuskalki | Test | Accuracy |
|---|---:|---:|
| zuberera | 1,067 | **94.19%** |
| mendebal-sortaldea | 2,304 | 90.58% |
| nafar-ipar-sartaldea | 346 | 88.15% |
| erdialde-sartaldea | 1,729 | 83.40% |
| erdialde-sortaldea | 876 | 79.11% |
| nafar-sortaldea | 267 | 75.66% |
| naflap-sortaldea | 246 | 71.95% |
| naflap-sartaldea | 127 | 69.29% |
| ekialde-nafarra | 125 | 68.00% |
| nafar-erdigunea | 87 | 49.43% |
| nafar-hego-sartaldea | 194 | 48.45% |
| mendebal-sartaldea | 77 | 48.05% |

**Model variants:**

| Variant | Filename | Accuracy | Size | vs original |
|---------|----------|---:|---:|---:|
| original | `azpieuskalki.bin` | 84.06% | 243MB | baseline |
| **quantized** | `azpieuskalki_q.bin` | **82.15%** | **22MB** | -1.91pp, 11× smaller |
| bucket=50K | `azpieuskalki_b50000.bin` | 83.47% | 129MB | -0.59pp, 1.9× smaller |
| **bucket=50K Q** | `azpieuskalki_b50000_q.bin` | **81.96%** | **5.5MB** | -2.10pp, 44× smaller |

## Usage

```python
import fasttext

# Load a model
model = fasttext.load_model("azpieuskalki.bin")

# Predict
text = "Neská jin düzü, Zuñ néska?"
labels, probs = model.predict(text, k=3)
print(labels[0].replace("__label__", ""), probs[0])
# Output: zuberera 0.978
```

Or use the `zeineuski` CLI from the [source repo](https://github.com/itzune/zeineuski):

```bash
uv run zeineuski predict --text "Gaur goizean goiz jaiki naiz"
```

## Web Demo

Try it in your browser — no server, no install:

**[itzune.eus/euskalkid](https://itzune.eus/euskalkid)** ([source](https://github.com/itzune/euskalkid))

34MB of fastText models running via WebAssembly. Works offline after first load.

## Training

Optimal hyperparameters (discovered via [pi-autoresearch](https://github.com/davebcn87/pi-autoresearch),
37 experiments over 3 sessions):

**Azpieuskalki 12-class:**
```bash
fasttext supervised -input train_azpieuskalki.txt -output azpieuskalki \
  -dim 200 -lr 0.2 -epoch 75 -wordNgrams 2 -minn 2 -maxn 6 -loss ns
```

Key insight: **NO autotune** — aggressive LR decay overfits to dominant classes.
**Character n-grams** (minn=2,maxn=6) capture Basque morphological patterns
(case endings, verb suffixes) that are dialect-specific (+9.4pp improvement).

## Changelog

### v2 (2026-06-11)
- Added 6,676 SÜ AZIA Zuberotarra sentences (pastoral scripts + blog articles)
- Zuberera training data: 750 → 7,117 sentences (1.9% → 14.3%)
- Zuberera per-class accuracy: 94.19%
- Overall 12-class accuracy: 84.06% (from 82.08% in v1)
- New model variants: q (22MB), b50000 (129MB), b50000_q (5.5MB)

### v1 (2026-06-08)
- Initial 12-class azpieuskalki model: 82.08% accuracy
- 9-class variant (min_samples=600): 83.55%

## License

MIT