---
license:
- cc0-1.0
- cc-by-4.0
- cc-by-2.0
- apache-2.0
- cc-by-sa-4.0
pretty_name: "IPAPACK++ Cleaned-Label Overlay (v1)"
task_categories:
- automatic-speech-recognition
language:
- en
- de
- fr
- es
- it
- pt
- nl
- sv
- pl
- cs
- sk
- hr
- ro
- mt
- eu
- gl
- ca
- be
- ru
- uk
- ba
- tr
- kk
- uz
- kmr
- rw
- sw
- so
- ar
- ur
- sd
- bn
- ta
- si
- hu
- lt
- th
- my
- vi
- yue
- zh
- ko
- ja
- ha
- yo
tags:
- phoneme-recognition
- ipa
- multilingual
- label-overlay
- ipapack
- g2p
- data-cleaning
- labels-only
size_categories:
- 1M<n<10M
---

# IPAPACK++ Cleaned-Label Overlay (v1)

A **labels-only, strictly additive** cleaned overlay on [IPAPACK++](https://huggingface.co/datasets/anyspeech/ipapack_plus_meta) (Zhu et al., ZIPA, ACL 2025): a regenerated `phones_v1_clean` label alongside the paper's original `phones`, a `drop_flag`, a per-utterance `sigs` list, and a per-row `license`. Audio is not bundled; original labels are preserved on every row.

> **Full documentation — the audit, methodology, signatures, and limitations — is forthcoming.** This card currently carries the licensing and basic-usage information only.

**Fields.** Train on `cut["supervisions"][0]["custom"]["phones_v1_clean"]`; skip rows where `…["custom"]["drop_flag"]` is `True`; per-row source license in `cut["custom"]["license"]`; paper baseline in `…["custom"].get("original") or …["custom"].get("phones")`. Audio is not included — re-pair from the public `anyspeech/ipapack_plus_*` shards by `cut.id`.

## Source corpora & licenses

This dataset is an **additive, labels-only overlay**. It redistributes **regenerated IPA phoneme labels (`phones_v1_clean`), orthographic transcript text, utterance IDs, and a Lhotse cut manifest — NO AUDIO.** Re-pair audio yourself from the sources below. Original IPAPACK++ `phones` are preserved on every row.

This is a **mixed-license** release. The applicable license is recorded **per row** in the `license` field. **Rows from ShareAlike sources are offered under CC-BY-SA and may *not* be treated as permissively licensed.**

> Primary citation: Zhu, J., Samir, F., Chodroff, E., Mortensen, D. R. *ZIPA: A Family of Efficient Models for Multilingual Phone Recognition.* ACL 2025. <https://aclanthology.org/2025.acl-long.961/> · arXiv:2505.23170

| Source | Rows | License | Attribution / citation |
|---|--:|---|---|
| Common Voice (`cv:*`) | 5,285,019 | CC0-1.0 | Mozilla Common Voice — <https://commonvoice.mozilla.org/> |
| Multilingual LibriSpeech (`mls:*`, SLR94) | 1,445,339 | CC-BY-4.0 | Pratap et al. (2020) — <https://www.openslr.org/94/> · labels regenerated |
| FLEURS (`fleurs:*`) | 155,927 | CC-BY-4.0 | Conneau et al. (2022), Google — <https://huggingface.co/datasets/google/fleurs> · labels regenerated |
| LibriSpeech (`openslr:librispeech/*`, SLR12) | 281,209 | CC-BY-4.0 | Panayotov et al. (2015) — <https://www.openslr.org/12/> · labels regenerated |
| AISHELL-1 (`aishell`, SLR33) | 120,078 | Apache-2.0 | Bu et al. (2017), arXiv:1709.05522 — <https://www.openslr.org/33/> |
| Kazakh KSC (`openslr:kazakh`, SLR102) | 147,165 | CC-BY-4.0 | Khassanov et al. (EACL 2021) — <https://www.openslr.org/102/> · labels regenerated |
| IISc-MILE Tamil (`openslr:tamil`, SLR127) | 77,136 | CC-BY-2.0 | Madhavaraj et al. (2022), arXiv:2207.13331 — <https://www.openslr.org/127/> · labels regenerated |
| **Bengali ASR (`openslr:bengali`, SLR53)** | 218,377 | **CC-BY-SA-4.0** | © 2016–2018 Google, Inc.; Kjartansson et al. (SLTU 2018) — <https://www.openslr.org/53/> · **ShareAlike** |
| **Javanese ASR (`openslr:javanese`, SLR35)** | 184,984 | **CC-BY-SA-4.0** | © 2016–2017 Google, Inc. (w/ Reykjavik Univ., Univ. Gadjah Mada) — <https://www.openslr.org/35/> · **ShareAlike** |
| **Sinhala ASR (`openslr:shinhala`, SLR52)** | 178,001 | **CC-BY-SA-4.0** | © 2016–2018 Google, Inc.; Kjartansson et al. (SLTU 2018) — <https://www.openslr.org/52/> · **ShareAlike** |
| **Kazakh KSD (`openslr:kazakh2/*`, SLR140)** | 196,944 | **CC-BY-SA-4.0** | Mansurova & Kadyrbek (2023), Al-Farabi Kazakh National Univ. — <https://www.openslr.org/140/> · source CC-BY-SA-3.0, **adapted labels offered under CC-BY-SA-4.0 (permitted ShareAlike upgrade)** |

**Excluded:** Magicdata — non-redistributable per IPAPACK++; confirmed absent from this release.

**ShareAlike notice.** The Bengali, Javanese, Sinhala, and Kazakh-KSD slices are offered under **CC-BY-SA-4.0** — their regenerated IPA labels are Adapted Material. (Bengali/Javanese/Sinhala sources are CC-BY-SA-4.0; the Kazakh-KSD source is CC-BY-SA-3.0, upgraded to 4.0 under the ShareAlike "this version or later" clause.) Changes were made (phoneme labels regenerated via grapheme-to-phoneme).

**G2P toolchain (credit, not a license obligation on the labels).** Labels were generated with OLaPh (Wirth, 2025; en/de/fr/cs), Epitran, phonemizer + espeak-ng (nl/sv), CharsiuG2P, pypinyin + pinyin-to-ipa, ToJyutping, viphoneme, PyThaiNLP, indic_nlp_library, and commonvoice-utils. espeak-ng is GPL-3.0 and commonvoice-utils is AGPL-3.0, used in-process during generation; per the FSF GPL FAQ, **program output is not covered by the program's copyright**, so no GPL/AGPL obligation attaches to these IPA label strings.

---

## Citation

Please cite **both** this overlay and the original IPAPACK++ paper.

```bibtex
@misc{kim2026ipapack_cleanup_v1,
  title  = {Cleaning IPAPACK++: A Surgical Audit of Multilingual Phoneme Labels},
  author = {Kim, Junehwi},
  year   = {2026},
  note   = {IPAPACK++ Cleaned-Label Overlay (v1), Hugging Face Datasets},
}
```

> Zhu, Jian and Samir, Farhan and Chodroff, Eleanor and Mortensen, David R. *ZIPA: A Family of Efficient Models for Multilingual Phone Recognition.* Proc. 63rd ACL 2025 (Vol. 1: Long Papers). <https://aclanthology.org/2025.acl-long.961/>

The label-cleanup work and this release are by Junehwi Kim; compute was a local 2080 Ti × 3.