2321575
Project Grant
Overview
Grant Description
SBIR Phase I: Artificial Intelligence (AI)-enabled African Language Database - The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is creating a tonally proficient Artificial Intelligence (AI)-enabled translation database for African languages.
There are no such product or service that can accurately translate African languages, as African languages have traditionally been under-resourced by Western corporations. By 2050, almost 25% of the Earth's population will be Sub-Saharan African and currently more than 60% of Africans are under 25 years old.
The African continent is projected to have $5.6 trillion in consumer and business spending by 2024 and the U.S. is investing over $350 million to expand digital access and literacy and promote U.S. corporate investment in the continent.
By expanding opportunities to accurately translate and learn African languages, this project will support economic growth for both the U.S. and African countries and support health and welfare by facilitating communication with African-speaking Americans and recent immigrants.
African languages are very diverse with more than 2000 distinct languages across the continent. They are difficult for non-native speakers to learn and for translation apps to correctly interpret, primarily due to the tonal and guttural sounds and slight pronunciation differences that make similar sounding words have completely different meanings.
The proposed AI-enabled database is first-of-its kind. The project will establish the data processing, model training, and database evaluation steps necessary to produce AI-enabled databases. The goal is to train a database to decipher these tonal shifts and ensure that the correct meaning is conveyed, beginning with a large dataset of correctly spoken audio and visual examples of words and phrases.
The primary objective of this project is to develop the entry-level, consistent, machine learning (ML) core functionalities and multimodal interactions in a database that can be utilized in the creation of other tonally based language ML/AI databases.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. Subawards are not planned for this award.
There are no such product or service that can accurately translate African languages, as African languages have traditionally been under-resourced by Western corporations. By 2050, almost 25% of the Earth's population will be Sub-Saharan African and currently more than 60% of Africans are under 25 years old.
The African continent is projected to have $5.6 trillion in consumer and business spending by 2024 and the U.S. is investing over $350 million to expand digital access and literacy and promote U.S. corporate investment in the continent.
By expanding opportunities to accurately translate and learn African languages, this project will support economic growth for both the U.S. and African countries and support health and welfare by facilitating communication with African-speaking Americans and recent immigrants.
African languages are very diverse with more than 2000 distinct languages across the continent. They are difficult for non-native speakers to learn and for translation apps to correctly interpret, primarily due to the tonal and guttural sounds and slight pronunciation differences that make similar sounding words have completely different meanings.
The proposed AI-enabled database is first-of-its kind. The project will establish the data processing, model training, and database evaluation steps necessary to produce AI-enabled databases. The goal is to train a database to decipher these tonal shifts and ensure that the correct meaning is conveyed, beginning with a large dataset of correctly spoken audio and visual examples of words and phrases.
The primary objective of this project is to develop the entry-level, consistent, machine learning (ML) core functionalities and multimodal interactions in a database that can be utilized in the creation of other tonally based language ML/AI databases.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. Subawards are not planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23515
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Culver City,
California
90232-3238
United States
Geographic Scope
Single Zip Code
ESM Global Productions was awarded
Project Grant 2321575
worth $275,000
from National Science Foundation in September 2023 with work to be completed primarily in Culver City California United States.
The grant
has a duration of 7 months and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Project Grant was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase I Programs.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I:Artificial Intelligence (AI)-Enabled African Language Database
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is creating a tonally proficient Artificial Intelligence (AI)-enabled translation database for African languages. There are no such product or service that can accurately translate African languages, as African languages have traditionally been under-resourced by Western corporations. By 2050, almost 25% of the earth’s population will be Sub-Saharan African and currently more than 60% of Africans are under 25 years old. The African continent is projected to have $5.6 trillion in consumer and business spending by 2024 and the U.S. is investing over $350 million to expand digital access and literacy and promote U.S. corporate investment in the continent. By expanding opportunities to accurately translate and learn African languages, this project will support economic growth for both the U.S. and African countries and support health and welfare by facilitating communication with African-speaking Americans and recent immigrants. _x000D_ _x000D_ _x000D_ African languages are very diverse with more than 2000 distinct languages across the continent. They are difficult for non-native speakers to learn and for translation apps to correctly interpret, primarily due to the tonal and guttural sounds and slight pronunciation differences that make similar sounding words have completely different meanings. The proposed AI-enabled database is first-of-its kind. The project will establish the data processing, model training, and database evaluation steps necessary to produce AI-enabled databases. The goal is to train a database to decipher these tonal shifts and ensure that the correct meaning is conveyed, beginning with a large dataset of correctly spoken audio and visual examples of words and phrases. The primary objective of this project is to develop the entry-level, consistent, Machine Learning (ML) core functionalities and multimodal interactions in a database that can be utilized in the creation of other tonally based language ML/AI databases._x000D_ _x000D_ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
LC
Solicitation Number
NSF 23-515
Status
(Complete)
Last Modified 9/22/23
Period of Performance
9/15/23
Start Date
4/30/24
End Date
Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2321575
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
JTYFSZKZ69B6
Awardee CAGE
8PQ15
Performance District
CA-37
Senators
Dianne Feinstein
Alejandro Padilla
Alejandro Padilla
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| Research and Related Activities, National Science Foundation (049-0100) | General science and basic research | Grants, subsidies, and contributions (41.0) | $275,000 | 100% |
Modified: 9/22/23