---
language:
- multilingual
language_bcp47:
- akp-AK
- any-Iv
- twi-GH
- avn-GH
- bqa-GH
- bim-GH
- biv-GH
- bib-GH
- bwu-GH
- ncu-GH
- dga-GH
- dag-GH
- adq-GH
- mzw-GH
- ewe-GH
- fat-GH
- ffm-GH
- acd-GH
- gjn-GH
- hau-GH
- kbp-GH
- xsm-GH
- xon-GH
- kma-GH
- kus-GH
- lef-GH
- maw-GH
- naw-GH
- Gur-GH
- nko-GH
- ntr-GH
- nzi-GH
- sig-GH
- sfw-GH
- lip-GH
- snw-GH
- sil-GH
- siwu-GH
- tpm-GH
- kdh-GH
- bov-GH
- vag-GH
tags:
- speech
- multilingual
- african-languages
- ghana
- phonemes
- tts
---

# Ghana Speech (Phonemized)

Preprocessed multilingual speech dataset from
[`ghananlpcommunity/ghana-speech`](https://huggingface.co/datasets/ghananlpcommunity/ghana-speech),
covering **42 Ghanaian and West African languages** with IPA phoneme transcriptions.

This dataset contains only the **metadata and phonemes** — no audio.
Use it together with the source dataset to load audio on-the-fly.

## Contents

Each language is a separate **config** (Parquet). Columns:

| Column | Type | Description |
|--------|------|-------------|
| `id` | string | Unique clip ID (matches audio IDs in the source dataset) |
| `text` | string | Raw orthographic transcription |
| `phon` | string | IPA phoneme transcription (espeak `lfn` voice) |
| `lang` | string | Language subset name (e.g. `Akuapem_Twi_twi`) |
| `lang_id` | int | Integer language ID (0-41) for speaker-conditioning slot |
| `dur` | float | Clip duration in seconds |
| `source_file` | string | Original source filename |
| `split` | string | `train` or `val` |

Repo-level files:

- **`lang_map.json`** — language name to lang_id mapping
- **`ghana_speech.json`** — mel normalisation stats (mel_mean, mel_std)
- **`lang_stats.json`** — per-language clip counts
- **`val_ids.json`** — list of validation clip IDs

## Filtering criteria

- Duration: 1.0s to 15.0s
- Phonemes: at least 2 non-space characters after phonemization
- Empty text: excluded

## Validation split

32 clips per language, stratified. Val clips have `split="val"` in the Parquet configs.

## Usage with Matcha-TTS

```python
from datasets import load_dataset, Audio

# Load phonemes for a specific language
ds = load_dataset("ghananlpcommunity/ghana-speech-phonemized", "Akuapem_Twi_twi", split="train")

# Load audio from the source dataset on-the-fly
audio_ds = load_dataset("ghananlpcommunity/ghana-speech", "Akuapem_Twi_twi", split="train")

# Combine: use phonemes from this dataset, audio from source
for phon_row, audio_row in zip(ds, audio_ds):
    phonemes = phon_row["phon"]
    audio = audio_row["audio"]["array"]
```

## Mel normalisation stats

```json
{"mel_mean": -5.728251241639019, "mel_std": 3.3875457364162376}
```

## Statistics

- **Total clips**: ~1,195,000
- **Languages**: 42
- **Train clips**: ~1,194,000
- **Val clips**: 1,344 (32 per language)

## License

Same as source dataset.