| --- |
| language: [lg] |
| license: cc0-1.0 |
| multilinguality: monolingual |
| task_categories: [text-to-speech, automatic-speech-recognition] |
| tags: [luganda, ganda, speech, tts, asr, african-languages, common-voice] |
| pretty_name: Luganda Speech Data (Pooled) |
| size_categories: [10K<n<100K] |
| --- |
| |
| # Luganda Speech Data (Pooled) |
|
|
| A **~111.4-hour** Luganda speech corpus, drawn from Mozilla Common Voice and |
| filtered to the `train` split. Part of the |
| [AfroNet](https://github.com/osinkolu/afronet-tts-data) multi-language TTS data |
| effort. |
|
|
| ## Source |
|
|
| **Mozilla Common Voice 26.0**, Luganda (`lg`) locale, accessed via the |
| [Mozilla Data Collective](https://mozilladatacollective.com/datasets/cmqinhruw00vinq07tohj4fd3) |
| mirror. 67,269 clips, 111.4h, source `dataset_id`/`source` = `common_voice`. |
|
|
| Common Voice is crowdsourced, scripted read speech: contributors record themselves |
| reading prompted sentences, and other contributors validate the recordings. The full |
| corpus splits into `train`/`dev`/`test`/`validated` (a superset of all three plus |
| extra validated-but-unsplit clips) -- only **`train`** is used here, same |
| held-out-partition policy we apply to DSN African Voices' splits. |
|
|
| **Why not WAXAL's `lug_tts` config too?** WAXAL's Luganda TTS config (~39h) is a |
| separate, independently-collected corpus with no evidence of overlap with Common |
| Voice -- unlike the Ethiopia/Shona/Lingala/Fulani cases elsewhere in this |
| collection, there's no matching-hours or matching-speaker-ID signal here. It remains |
| a candidate for a future top-up if more Luganda hours are wanted. |
| |
| All audio is standardized to **16 kHz mono FLAC** (lossless), 1–30 second clips. |
| Source audio is MP3, decoded directly via `soundfile` (no external decoder needed). |
| |
| ## Format |
| |
| The dataset ships as **WebDataset-style tar shards** (`shards/shard-00000.tar` …, ~1 GB |
| each, one `{key}.flac` file per clip) plus a single manifest (`manifest.parquet` / |
| `manifest.jsonl`): |
| |
| | Column | Description | |
| |---|---| |
| | `key`, `shard` | which tar file + entry holds this clip's audio | |
| | `text` | transcript (native Luganda script), from Common Voice's `sentence` field | |
| | `duration` | seconds | |
| | `source` | always `common_voice` | |
| | `dataset_id` | always `0` | |
| | `split` | `train` / `val` (250 clips held out for evaluation) | |
| | `speaker_id` | Common Voice's `client_id` | |
| | `gender` | speaker-reported gender where available (Common Voice's `gender` field, e.g. `male_masculine`/`female_feminine`) | |
| | `dbfs`, `clip_ratio`, `sil_ratio` | cheap DSP quality proxies: loudness, fraction of clipped samples, fraction of near-silent frames | |
| | `has_disfluency` | always `false` | |
| |
| ## Usage |
| |
| ```python |
| from huggingface_hub import hf_hub_download |
| import pandas as pd, tarfile, io, soundfile as sf |
| |
| mp = hf_hub_download("Professor/luganda-speech-data", "manifest.parquet", repo_type="dataset") |
| df = pd.read_parquet(mp) |
| |
| row = df.iloc[0] |
| shard_path = hf_hub_download("Professor/luganda-speech-data", f"shards/{row.shard}", repo_type="dataset") |
| with tarfile.open(shard_path) as tar: |
| audio_bytes = tar.extractfile(f"{row.key}.flac").read() |
| arr, sr = sf.read(io.BytesIO(audio_bytes)) |
| ``` |
| |
| The tar shards are also directly readable by the [`webdataset`](https://github.com/webdataset/webdataset) |
| library for streaming training pipelines. |
| |
| ## Intended use & limitations |
| |
| Built for **Luganda TTS/ASR research**, in particular as finetuning data for a |
| multilingual TTS model that doesn't natively support Luganda. Common Voice audio is |
| crowdsourced (variable recording equipment/environment across contributors) but |
| validated by community review, so quality is generally clean read speech. This is a |
| **research aggregation**; usage should respect Common Voice's own terms. |
| |
| ## License |
| |
| CC0 1.0 Universal (public domain dedication), per the upstream Common Voice release. |
| |
| ## Acknowledgments |
| |
| Deep thanks to **Mozilla Common Voice** and its Luganda-speaking contributors for |
| the source corpus, and to the **Mozilla Data Collective** for hosting it. |
|
|
| This dataset was pooled by **Victor Olufemi and LyngualLabs** as part of the |
| [AfroNet](https://github.com/osinkolu/afronet-tts-data) multi-language TTS data effort. |
|
|
