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Task: N/A
Release Date: 9/15/2026
Format: WAV, EAF, TextGrid, MD, CSV
Size: 1014.22 MB
This collection contains sixteen Shiwilu narratives and songs with transcription, Spanish translation, and English translation time-aligned in ELAN. It is the most richly and extensively annotated collection in the dataset, with 9,016 annotations distributed across tiers for words (words), Shiwilu transcription (trs_Shiwilu), Spanish transcription (trs_Spanish), free Spanish translation (ft_Spanish), free English translation (ft_English), and notes. The materials include two versions of basket-making, narratives about the tiger, two versions of the shapishico, the dog and the manchari, the worm and the breast, the renaco, the tapir, frogs, the wampi, the Jívaro, and two people from the community. The collection also includes two songs, one about the stars and another about a cow. Shiwilu is a severely endangered language with very few remaining speakers, making this collection a valuable source of language documentation. The materials were recorded in Yurimaguas and Iquitos, Loreto, Peru. The entire collection was documented by Alonso Vásquez-Aguilar.
Licensing
Licencia Chana 2.0 — Licence for Peruvian Indigenous Language Documentation Collections
https://github.com/rzariquiey/licencia-chanaRestrictions/Special Constraints
ACCESS IS GRANTED ON REQUEST. Requesters must identify themselves and state their institutional affiliation. The donor reviews and approves or declines each request individually. This dataset is released under the Licencia Chana 2.0, not under a Creative Commons licence. Download is direct and unrestricted, but use is subject to the following terms. PERMITTED WITHOUT FURTHER AUTHORISATION - Academic research and publication, with attribution. - Teaching and educational use, with attribution. - Language revitalisation work by the source communities and by organisations working with them. - Evaluating and benchmarking existing speech or language models, with attribution. - Non-production academic machine-learning experimentation, provided that (a) the resulting model is not deployed in production, (b) model weights are not released, and (c) any results published cite this collection. REQUIRES PRIOR WRITTEN AUTHORISATION FROM THE DONOR - Training models intended for production or public release. - Release or distribution of model weights derived from this material. - Any commercial use. - Redistribution of the dataset, in whole or in part, on any other platform. ATTRIBUTION Cite as: Alonso Vásquez-Aguilar (donor). Shiwilu: Narratives and Songs. Mozilla Data Collective. RIGHT OF WITHDRAWAL Speakers retain the right to withdraw their recordings from this collection at any time. This is the principal reason a Creative Commons licence was not used: CC licences are irrevocable and cannot accommodate this commitment. Contact for authorisations: [email protected]
Forbidden Usage
- You agree not to attempt to determine the identity of the pseudonymised speakers in this dataset, nor to link the speaker codes (S01, S02...) to real individuals. - Any attempt to clone, synthesise or imitate the voices of the speakers in this dataset is forbidden. - Training models intended for production deployment or public release is forbidden without prior written authorisation from the donor. This includes releasing model weights trained wholly or partly on this material. - Commercial use of any kind is forbidden without prior written authorisation. - Redistribution of this dataset, in whole or in part, on any other platform or in any other repository is forbidden without prior written authorisation. - Use of this material in ways that misrepresent, decontextualise or commercially exploit the cultural knowledge it contains is forbidden. Note on machine learning: this is not a blanket prohibition on ML research. Evaluating and benchmarking existing models on this data is permitted, and so is non-production academic experimentation, provided the model is not deployed, the weights are not released, and the results cite the collection. What requires authorisation is production training and weight release. The reason is that the consent forms signed before approximately 2020 do not mention AI training and cannot reasonably be read as covering it; the communities have not yet been consulted on this point. Contact for authorisations: [email protected]
Ethical Review
All recordings in this collection were made with the informed consent of the speakers, obtained in the field at the time of recording. Signed consent forms are held by the donor at the Pontificia Universidad Católica del Perú and are available to the MDC team on request. Speakers are identified by code (S01, S02...) rather than by name, in file names, in the annotation tiers of the ELAN files, and in all accompanying documentation. Contributors are acknowledged collectively in each collection's documentation, without linking any name to any specific recording or code. A small number of individuals appear under their own names because they asked to be credited as authors of the material; this is stated explicitly in the documentation of the collections concerned. Material judged sensitive was withheld from deposit entirely rather than published under restriction. Collections involving funerary practice, medicinal knowledge, ritual knowledge, or extended life histories of identifiable individuals are published under restricted access with individual review of each request. One point remains open and is declared here rather than glossed over: the consent forms signed before approximately 2020 do not mention the use of recordings for training artificial intelligence models. They cannot reasonably be read as covering it. The communities have not yet been consulted on this specific question. Until that consultation takes place, production model training is not authorised, and the licence reflects this.
Intended Use
The most richly annotated collection in this deposit, with over 9,000 annotations and both Spanish and English translation, in a Cahuapanan language with very few remaining speakers. Intended for computational morphology, for discourse research, and for preservation.
