--- license: cc0-1.0 pretty_name: VoxCommunis Artifacts task_categories: - automatic-speech-recognition tags: - phonetics - multilingual source_datasets: - mozilla-foundation/common_voice_17_0 - pacscilab/VoxCommunis language_bcp47: - ab - am - ba - be - bg - bn - ca - ckb - cs - cv - dv - el - eu - fr - gn - ha - hi - hsb - hu - hy-AM - id - it - ja - ka - kk - kmr - ko - ky - lij - lt - ml - mn - mr - mt - myv - nan-tw - nl - pa-IN - pl - pt - ro - ru - rw - sk - sl - sq - sr - sv-SE - sw - ta - th - tk - tr - tt - ug - uk - ur - uz - vi - yo - yue - zh-CN - zh-HK --- # VoxCommunis Artifacts The data artifacts used to train and evaluate the MauBERT models, introduced by the [MauBERT paper](https://aclanthology.org/2026.acl-long.24/): manifests, frame-level phone alignments, per-language phone inventories, and the language table. Companion model repositories: - [`coml/maubert-feat`](https://huggingface.co/coml/maubert-feat) — articulatory feature prediction. - [`coml/maubert-phone`](https://huggingface.co/coml/maubert-phone) — IPA phone prediction. ### No audio is included The recordings come from [Common Voice 16.1](https://commonvoice.mozilla.org/en/datasets), which you must download yourself; the phone annotations come from [VoxCommunis](https://huggingface.co/datasets/pacscilab/VoxCommunis). This repository only ships the derived annotations and the file lists that tie them to the Common Voice audio. ### Language split At the time of download (August 2024), there were 63 languages, out of which 5 languages were held-out as development languages (Swahili, Tamil, Thai, Turkish and Ukrainian) and 3 languages were _unused_ due to their presence in [ZRC2017](https://zerospeech.com/tasks/task_1/benchmarks_datasets/#zrc2017-and-abx17), that is the test languages (French and two Chinese variants). ## Files - `vox_communis_languages.tsv`: The 63 VoxCommunis languages, with family, branch, duration in minutes (before and after 50h capping), and a `split` column marking the 55 pre-training languages (`train`) against the 8 held-out languages used as development (`dev`) or test (`test`) languages. - `inventories.jsonl`: The IPA phone inventories, one language per line, `{"language": , "name": , "phones": [...]}`, exactly as they come out of the VoxCommunis alignments (after character normalisation). - `canonical_inventories.jsonl`: The same inventories, with every phone replaced by its [PanPhon](https://github.com/dmort27/panphon) canonical representative (`maubert.data.FeatureDecoder.segment_to_representative`) — these are the segments the models actually index. **This is the file the library reads**: it is required to reduce the phone head when extracting features from the phone projection layer, for **both** model variants. - `full_dataset/multilingual-{train,dev,test}.{tsv,align}`: The original multilingual Common Voice splits (**not used**), plus the reduced subsets used for validation and testing of the multilingual pre-training, namely `multilingual-dev-1h` and `multilingual-test-2h`. - `full_dataset/{train,dev,test,train-50h}/{manifests,alignments}/.{tsv,align}`: The same data as above, but separated by both split and language. **`train-50h` is the duration-capped split actually used during multilingual pre-training.** - `dev_languages/{train-10min,train-1h,train-10h,dev,test}/{manifests,alignments}/`: The extracted splits for the 5 held-out development languages used for zero- and few-shot acoustic unit discovey (see [task 1](https://zerospeech.com/tasks/task_1/tasks_goals/) of ZeroSpeech challenge series), with the corresponding ABX `items/` for the `dev` (released but never used due to the high number of speakers) and `test` sets. Manifests (`.tsv`) list audio files: the first line is the corpus root, every subsequent line is `\t`. As shipped, the root is the placeholder `/path/to/cv-corpus-16.1` and every path is a bare filename; see [Re-rooting the manifests](#re-rooting-the-manifests) to point them at your copy of the corpus. Alignments (`.align`) carry the frame-level phone labels, one line per utterance, `\t`. ## Usage Install [`maubert`](https://github.com/bootphon/maubert), then download this repository: ```python from huggingface_hub import snapshot_download data_dir = snapshot_download("coml/vox-communis-artifacts", repo_type="dataset") ``` ### Re-rooting the manifests Every manifest ships with the placeholder root `/path/to/cv-corpus-16.1` on its first line, and its rows are bare `.wav` filenames. Point the manifests at your own copy of the corpus before training: ```python from maubert.data.io import update_manifest update_manifest( f"{data_dir}/full_dataset/multilingual-train.tsv", "/data/cv-corpus-16.1", file_extension=".mp3", ) ``` Matching is done on the file stem, which is identical between the original `.mp3` and the converted `.wav`, so this works against an unconverted Common Voice release and against any directory layout under the root you pass — only pass the extension your copy actually uses. **However, beware that MauBERT models were trained on and accept `.wav` files only.** The helper rewrites the manifest **in place** and leaves the previous version alongside it as `multilingual-train.tsv.bak`; it raises if that backup already exists, so run it once per download. It also raises if any utterance in the manifest is missing from your tree. Once re-rooted, the files map directly onto the `data` section of `configs/train_feat.yaml` and `configs/train_phone.yaml` in the [`maubert`](https://github.com/bootphon/maubert) repository — `full_dataset/train-50h/{manifests,alignments}` as `train_manifest` / `train_alignment` and `full_dataset/multilingual-dev-1h.{tsv,align}` as `val_manifest` / `val_alignment`, while `canonical_inventories.jsonl` fills the `downstream.inventory_file` field used by the monolingual configs. ### Looking up a language inventory ```python from maubert.data.phone_dataset import get_language_inventory # Either the language name or its BCP-47 code inventory = get_language_inventory(f"{data_dir}/canonical_inventories.jsonl", "italian") ``` ## Citing Please cite MauBERT alongside [Common Voice](https://commonvoice.mozilla.org/en/datasets) and [VoxCommunis](https://huggingface.co/datasets/pacscilab/VoxCommunis): ```bibtex @inproceedings{ortiztandazo-etal-2026-maubert, title = "{M}au{BERT}: Universal Phonetic Inductive Biases for Few-Shot Acoustic Units Discovery", author = "Ortiz Tandazo, Angelo and Khentout, Manel and Benchekroun, Youssef and Hueber, Thomas and Dupoux, Emmanuel", editor = "Liakata, Maria and Moreira, Viviane P. and Zhang, Jiajun and Jurgens, David", booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)", month = jul, year = "2026", address = "San Diego, California, United States", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2026.acl-long.24/", doi = "10.18653/v1/2026.acl-long.24", pages = "568--585", ISBN = "979-8-89176-390-6", } ```