---
language:
- pt
license: mit
pretty_name: "Pho-BP: Phonological Benchmark for Brazilian Portuguese"
task_categories:
- text-classification
- token-classification
tags:
- phonology
- phonological-awareness
- brazilian-portuguese
- literacy
- tabular
- datasets
size_categories:
- 10K<n<100K
configs:
- config_name: rhyme
  default: true
  data_files:
  - split: train
    path: train/rhyme_train.csv
  - split: validation
    path: validation/rhyme_validation.csv
  - split: test
    path: test/rhyme_test.csv
- config_name: syllable
  data_files:
  - split: train
    path: train/syllable_train.csv
  - split: validation
    path: validation/syllable_validation.csv
  - split: test
    path: test/syllable_test.csv
- config_name: initial_phoneme
  data_files:
  - split: train
    path: train/initial_phoneme_train.csv
  - split: validation
    path: validation/initial_phoneme_validation.csv
  - split: test
    path: test/initial_phoneme_test.csv
- config_name: reading_error
  data_files:
  - split: train
    path: train/reading_error_train.csv
  - split: validation
    path: validation/reading_error_validation.csv
  - split: test
    path: test/reading_error_test.csv
---

# Pho-BP

**Pho-BP (Phonological Benchmark for Brazilian Portuguese)** is a complete multitask benchmark for evaluating phonologically informed representations in Brazilian Portuguese. This release contains **46,000 labeled examples** distributed across four tasks and fixed train/validation/test partitions.

## Tasks and sizes

| Configuration | Task | Train | Validation | Test | Primary metrics |
|---|---|---:|---:|---:|---|
| `rhyme` | Binary rhyme detection | 10,000 | 1,000 | 1,000 | Accuracy, macro-F1 |
| `syllable` | Character-boundary syllable segmentation | 8,000 | 1,000 | 1,000 | Boundary/token F1 |
| `initial_phoneme` | Initial phoneme classification | 15,000 | 1,500 | 1,500 | Accuracy, macro-F1 |
| `reading_error` | Reading-error type classification | 5,000 | 500 | 500 | Accuracy, macro-F1 |

The rhyme splits are exactly balanced. The syllable task has an overall mean word length of **8.70 characters**. Initial-phoneme training is exactly balanced across 24 classes; validation and test differ by at most one example per class. Reading errors use a deliberately imbalanced distribution: 45% phoneme substitution, 25% omission, 20% orthographic confusion, and 10% insertion.

## Public-release provenance

The lexical tasks were reconstructed from the open Brazilian Portuguese lexicon `fserb/pt-br` (MIT), ranked by its ICF frequency resource. Pronunciations were generated with the deterministic Pho-BP rule-based Brazilian Portuguese G2P procedure and syllable boundaries with Pyphen `pt_BR`.

The row-level child oral-reading corpus described in the research manuscript was not available among the supplied files. To avoid fabricating observations attributed to children or publishing potentially identifying educational records, the `reading_error` configuration is a **complete privacy-preserving rule-based public release** that instantiates the same four error categories without participant identifiers. The field `source_type` makes this provenance explicit. The baseline JSON files preserve the values reported in the thesis and identify them as reported results; they were not recomputed on this reconstructed public release.

## Loading from Hugging Face

```python
from datasets import load_dataset

rhyme = load_dataset("YOUR_NAMESPACE/pho-bp", "rhyme")
syllable = load_dataset("YOUR_NAMESPACE/pho-bp", "syllable")
initial = load_dataset("YOUR_NAMESPACE/pho-bp", "initial_phoneme")
reading_error = load_dataset("YOUR_NAMESPACE/pho-bp", "reading_error")
```

The YAML metadata above maps each configuration to its three CSV files, so no custom loading script is required.

## Schemas

### Rhyme detection

`id`, `word1`, `word2`, `ipa1`, `ipa2`, `rhyme_key1`, `rhyme_key2`, `label`, `source`.

`label=1` indicates equal phonetic rhyme keys; `label=0` indicates different keys.

### Syllable segmentation

`id`, `word`, `ipa`, `syllables`, `boundary_labels`, `num_syllables`, `source`.

`boundary_labels` is a JSON array of length `len(word)-1`; value `1` marks a syllable boundary after that character. Example: `casa` → `[0, 1, 0]`.

### Initial phoneme

`id`, `word`, `ipa`, `initial_phoneme`, `label_id`, `source`.

The 24 classes in label-id order are: `a`, `k`, `p`, `e`, `s`, `d`, `m`, `i`, `ʁ`, `t`, `b`, `f`, `l`, `v`, `g`, `o`, `n`, `ʒ`, `ʃ`, `u`, `z`, `ɲ`, `ʎ`, `tʃ`.

### Reading error

`id`, `target_word`, `observed_reading`, `target_ipa`, `observed_ipa`, `error_type`, `error_span`, `generation_rule`, `source_type`.

The four labels are `phoneme_substitution`, `omission`, `orthographic_confusion`, and `insertion`.

## Evaluation

Each file in `scripts/` accepts a gold CSV and a prediction CSV. Prediction files must contain `id` and `prediction`, except syllable segmentation, which accepts `id` plus `prediction` containing either a JSON boundary array or a hyphenated segmentation.

```bash
python scripts/evaluate_rhyme.py   --gold test/rhyme_test.csv   --predictions predictions/rhyme_predictions.csv
```

## Baselines

`baselines/` contains the results reported for BERTimbau, XLM-R, and Lacium Flower. Classification task entries contain accuracy and macro-F1; syllable segmentation contains token/boundary F1. All values are percentages and correspond to the mean of three runs as reported in the thesis.

## Intended use

Pho-BP is intended for research on Brazilian Portuguese phonology, representation learning, multitask learning, literacy-support NLP, probing, and controlled comparison of models. It is not a diagnostic instrument and must not be used to make clinical, educational-placement, or high-stakes decisions about individual learners.

## Limitations

Pronunciations and syllabification are generated automatically and may reflect dialect-neutral or tool-specific conventions. Rhyme keys depend on the rule-based G2P stress assignment. The public reading-error subset is rule-based rather than a substitute for ecologically valid, consented oral-reading data. Results reported on the original internal benchmark should not be presented as newly measured results on this release.

## Citation

Use `CITATION.cff` or cite the dataset as:

> Gomes da Cruz Junior, G., & Fidalgo, R. N. (2026). *Pho-BP: Phonological Benchmark for Brazilian Portuguese* (Version 1.0.0) [Dataset].

## License

MIT. See `LICENSE`, including the attribution notice for the source lexicon.