SBIR Phase I: Artificial Intelligence (AI)-Enabled African Language Database

SBIR 第一阶段：人工智能 (AI) 支持的非洲语言数据库

• 批准号: 2321575
• 负责人: Michael Odokara
• 金额: $ 27.5万
• 依托单位: ESM GLOBAL PRODUCTIONS LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321575&HistoricalAwards=false
• 关键词: SBIR; Phase; Artificial; Intelligence; AI

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.

小型企业创新研究(SBIR)第一阶段项目的更广泛/商业影响是创建一个精通人工智能(AI)的非洲语言翻译数据库。没有这样的产品或服务可以准确地翻译非洲语言，因为非洲语言传统上一直被西方公司资源不足。到2050年，几乎25%的地球人口将是撒哈拉以南非洲人，目前超过60%的非洲人年龄在25岁以下。预计到2024年，非洲大陆的消费者和企业支出将达到5.6万亿美元，美国将投资超过3.5亿美元，以扩大数字接入和扫盲，并促进美国企业在非洲大陆的投资。通过扩大准确翻译和学习非洲语言的机会，该项目将支持美国和非洲国家的经济增长，并通过促进与讲非洲语言的美国人和新移民的交流来支持健康和福利。非洲语言非常多样，在整个非洲大陆有2000多种不同的语言。对于非母语人士来说，它们很难学习，翻译应用程序也很难正确解释，主要是因为它们的声调和喉音，以及轻微的发音差异，使得发音相似的单词具有完全不同的含义。拟议的人工智能数据库是此类数据库中的第一个。该项目将建立产生人工智能数据库所需的数据处理、模型培训和数据库评估步骤。其目标是训练一个数据库，以破译这些音调变化，并确保传达正确的含义，从单词和短语的正确说话的音频和视频示例的大型数据集开始。这个项目的主要目标是在一个数据库中开发入门级的、一致的、机器学习(ML)核心功能和多模式交互，可用于创建其他基于声调的语言ML/AI数据库。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。