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Find similar grantsNatural Language Processing (NLP) Program is sponsored by Lacuna Fund. This program funds the creation, augmentation, or updating of AI training and evaluation datasets for underserved populations and languages, specifically for Natural Language Processing (NLP) in low-resource languages and underrepresented cultures.
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Timely and accurate access to information – spoken or written – in one’s own language is a must to enable full participation in the digital world. Translations, the ability to understand and synthesize speech, and many other AI-enabled applications in the field of natural language processing (NLP) require training and evaluation data that does not exist for many languages, some spoken by millions of people around the world.
The ability to communicate and be understood in one’s own language is a prerequisite to digital and societal inclusion. Natural language processing (NLP) techniques have enabled critical applications to achieve this—to improve education, financial inclusion, healthcare, agriculture, communication, and disaster response, among many other areas.
However,a gap in openly accessible datasets outside of English and other Indo-European languageshas prevented breakthroughs based on NLP technologies. Labeled data and speech corpora remain a key element of this gap, as well as the availability of corpora that can be used in transfer learning or semi-supervised approaches.
## NaijaVoices: Curation of Speech Datasets in Igbo, Hausa, and Yoruba Lacuna Fund’s efforts in NLP build on a recent groundswell of momentum to create better and more open NLP tools in underserved languages from ML community members, including recent academic workshops, volunteer collaborations, innovative academic programs, and other efforts.
To complement and support these efforts, Lacuna Fund supports open training and evaluation datasets for NLP in underserved languages. OurTechnical Advisory Panel(TAP), who is responsible for identifying data gaps, developing the RFP, and reviewing and selecting proposals, has identified needs for labeled datasets in the following areas.
However, Lacuna Fund RFPs are intentionally open, to encourage new and innovative ideas that we may not have identified.
**The TAP sees a need for datasets that enable better execution of core NLP tasks in African languages,including but not limited to the following:** * Speech corpora, particularly enabling automated voice recognition that allows illiterate or otherwise underprivileged groups of persons to access information and/or services; * Labeled and unlabeled text corpora for use as training data; * Parallel corpora for machine translation; * Corpora to support fundamental NLP tasks, such as named entity recognition (NER), part of speech tagging, embeddings, etc.; * Datasets for key downstream NLP tasks, such as question answering and conversational AI, sentiment analysis datasets, or technology for language education; * Datasets to improve the performance of NLP tasks on code-switched text or speech.
#### **More broadly, there is also a need for:** * Augmentation of existing datasets in all areas to decrease bias (such as gender bias or other types of bias or discrimination) or increase the usability of NLP technology in low- and middle-income contexts; * More benchmark data for NLP tasks in underserved languages or to inform multilingual models; * Innovative datasets, such as video or audio captioning or other image-text interactions; * Domain-specific creation or augmentation of text and speech datasets, such as digit datasets, place names, or specific word pairs or sentences, that enable applications with significant social impact.
According to the current listing, eligibility includes: Non-profit entities, research institutions, for-profit social enterprises, or teams thereof. Confirm the full requirements in the official notice before applying.
The current listing shows up to $100,000 for smaller projects, $100,000–$250,000 for larger projects (from a total pool of approximately $1 million USD). Verify award ceilings, matching requirements, and allowable costs in the official notice.
Natural Language Processing (NLP) Program is funded by Lacuna Fund. Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
Lacuna Fund Natural Language Processing (NLP) Program is a grant from Lacuna Fund that funds the creation, augmentation, or updating of AI training and evaluation datasets for underserved populations and languages. Awards range from up to $100,000 for smaller projects to $100,000–$250,000 for larger projects, from a total pool of approximately $1 million USD. Eligible applicants include nonprofits, research institutions, for-profit social enterprises, and teams thereof; individuals must apply through an institutional sponsor. Organizations must be headquartered in the country or region where data will be collected and have a mission supporting societal good. Partnerships are strongly encouraged. The 2024 NLP program is managed in partnership with Centro Nacional de Inteligencia Artificial (CENIA).
Lacuna Fund is a first-of-its-kind multi-funder collaboration formed in 2020 (and transferred to Global South leadership in July 2025) to fill gaps in data used to train Machine Learning models, making ML and AI more representative, accurate, equitable, and accessible to underserved communities worldwide. The Fund supports grantees to create high-quality, openly accessible machine-learning datasets that serve urgent problems in Africa, Asia, and Latin America across four thematic areas: agriculture (crop monitoring, smallholder farming, soil and weather datasets); language (low-resource language NLP datasets, including text, speech, and machine translation across 29+ African languages and indigenous Latin American languages); health (clinical AI datasets, disease surveillance, epidemiology); and climate (climate adaptation, weather prediction, ecosystem monitoring). Following the July 2025 leadership transition, the Fund is now governed by ACTS (African Centre for Technology Studies), CENIA (Chile's National Centre for AI), Masakhane, and the University of Pretoria's Data Science for Social Impact Research Group — putting Global South institutions firmly in control of priorities, calls, and grantmaking decisions. Calls are issued in cohorts by thematic area; the 2026 cohort emphasizes climate datasets and continued investment in African language NLP.
Lacuna Fund is a multi-funder, multi-stakeholder collaboration formed in 2020 to fill gaps in data used to train Machine Learning (ML) models, making ML and AI more representative, accurate, equitable, and accessible to underserved communities globally. The fund issues thematic calls for dataset creation across four priority domains: (1) Agriculture - datasets supporting AI for smallholder farming, crop monitoring, livestock health, pest detection, and food security in low-resource regions; (2) Climate - datasets enabling AI for climate adaptation, biodiversity monitoring, environmental change detection, and disaster response; (3) Health - datasets for AI in disease surveillance, diagnostic tools, maternal/child health, and health systems in low and middle income countries; and (4) Natural Language Processing - datasets advancing AI in low-resource and African languages. To date, Lacuna Fund has enabled creation of over 75 new ML datasets including 18 newly published datasets in 2025. Funders include Google.org, Rockefeller Foundation, International Development Research Centre (IDRC), GIZ on behalf of the German Federal Ministry for Economic Cooperation and Development (BMZ), and additional supporters. Calls are issued on rolling thematic schedule with secretariat-managed application cycles.
NVIDIA Graduate Fellowship Program is a grant from NVIDIA providing up to $60,000 per award to PhD students conducting research that advances accelerated computing and its applications. Now in its 25th year, the program invites nominations from doctoral students pushing the boundaries of artificial intelligence, robotics, autonomous vehicles, and related fields. Recipients receive not only research funding but also access to NVIDIA technology, products, and engineering expertise, along with a mandatory in-person summer internship. Students are nominated by their faculty advisors and selected based on academic achievement and research area alignment.
CalSEED Concept Award is a grant from the California Energy Commission that provides $150,000 in funding to early-stage clean energy innovators in California. The program targets individuals, businesses, and nonprofits developing hardware, software, or integrated solutions at Technology Readiness Levels 2-4. Eligible technology areas rotate each cycle and have included battery recycling and reuse, long-duration energy storage, medium- and heavy-duty vehicle electrification, industrial electrification, and advanced EV charging. Applicants must be located in California, have under $1 million in private funding, and propose innovations that benefit California ratepayers. Concept Award winners also receive professional development resources and access to accelerator programs, and may compete for a subsequent $450,000 Prototype Award.
NIST SBIR Phase I - Advanced Manufacturing and Robotics is sponsored by National Institute of Standards and Technology. NIST SBIR Phase I - Advanced Manufacturing and Robotics is a grant from the National Institute of Standards and Technology (NIST) that funds small businesses with innovative research and technology ideas in advanced manufacturing and robotics.