LDC-IL Launches 16 New Datasets to Advance AI Research in Indian Languages
The Linguistic Data Consortium for Indian Languages (LDC-IL), a Scheme of the Ministry of Education, recently organized the 8th Project Advisory Committee meeting in Mysuru. During the meeting, the LDC-IL launched 16 new datasets in Indian languages to support research in Artificial Intelligence (AI) and Machine Learning (ML). These datasets aim to develop new technologies in Indian languages, such as Automatic Speech Recognition and Live Voice Translation, while improving the quality of results. The datasets cover 12 scheduled languages, including Hindi, Bengali, Tamil, Marathi, and Kannada, and two variants of Indian English.
Indian Languages Get a Boost with New Datasets for AI and ML
The launch of the 16 new datasets by the Linguistic Data Consortium for Indian Languages (LDC-IL) is expected to have a significant impact on the development of AI and ML technologies in Indian languages. These datasets will help researchers and developers create innovative applications and tools to enhance the use of Indian languages in various fields. With languages like Hindi, Bengali, Tamil, and Kannada now having dedicated datasets, the quality of AI-driven tools and technologies in these languages will see a significant improvement. This development is expected to boost research and development efforts in Indian languages across academia and industry.
LDC-IL Releases First-Ever Datasets for Chhattisgarhi Language
In a significant move, the Linguistic Data Consortium for Indian Languages (LDC-IL) released two datasets for Chhattisgarhi, a mother tongue often grouped with Hindi. This marks the first time that dedicated datasets have been made available for Chhattisgarhi, highlighting the government’s commitment to promoting and supporting education and technology in all mother tongues of India. This step aligns with the recommendations of the National Education Policy 2020, which emphasizes the importance of recognizing and developing mother tongues across the country. The release of these datasets will pave the way for research and development in Chhattisgarhi language technology.
Datasets for Indian Languages to Drive Research and Development
The newly launched datasets by the Linguistic Data Consortium for Indian Languages (LDC-IL) are expected to fuel research and development activities in all Indian languages. Academia and industry alike will benefit from these datasets as they provide a solid foundation for creating AI and ML applications specific to Indian languages. The applications developed based on these datasets will not only enhance the quality and accuracy of language-based technologies but also contribute to the promotion and preservation of Indian languages. Additionally, these datasets can also serve as benchmarks for testing AI and Generative AI-based technologies, further propelling innovation in this field.
LDC-IL Expands Data Repository with 16 New Datasets in Indian Languages
The Linguistic Data Consortium for Indian Languages (LDC-IL) has added 16 new datasets to its data repository, strengthening its position as the largest repository of Curated Text and Speech resources in Indian languages for linguistic research, AI, and ML. With the launch of these datasets, the portal now offers a total of 57 datasets covering 21 Indian languages. The uniqueness of the LDC-IL datasets lies in their collection process, as they are not crowdsourced but instead collected from verified sources by language experts. These datasets serve as valuable resources for training, benchmarking, and testing AI-based technologies, furthering the growth of research and development in Indian languages.
Analyst comment
Positive news: The launch of 16 new datasets by the Linguistic Data Consortium for Indian Languages is expected to have a significant impact on the development of AI and ML technologies in Indian languages. It will boost research and development efforts, enhance the quality of AI-driven tools, and contribute to the promotion and preservation of Indian languages. The datasets will fuel innovation in academia and industry and serve as benchmarks for testing AI technologies.
