China News Service, Lhasa, October 5 (Gonggalaisong) Recently, China's first Tibetan language model upgrade and iteration and simultaneous interpretation research and development promotion conference was held in Hohhot, Inner Mongolia Autonomous Region. The conference focused on core issues such as the optimization and upgrading of Tibetan artificial intelligence technology and the application of multilingual simultaneous interpretation, and coordinated the deployment of the research and development and promotion of ethnic language intelligent technology to help high-quality development of the digital economy in ethnic minority areas.
Due to its special language structure, large dialect differences, and scarce high-quality corpus resources, Tibetan has long been a low-resource problem in the field of natural language processing. The precise and universal development of Tibetan intelligent technology has always been a key research direction in the industry. As China's first major Tibetan language model, DeepZang has continued to break through technical bottlenecks since its development, and has continuously optimized Tibetan multi-dialect adaptation, precise semantic recognition, and offline scenario applications. It has promoted the leapfrog upgrade of Tibetan intelligent technology from "basically usable" to "accurate and easy to use", filled a number of industry technology gaps, and improved China's national language artificial intelligence technology system.
This meeting made it clear that the research and development of Tibetan artificial intelligence technology always adheres to the application orientation and is based on the actual needs of ethnic minority areas. In the future, the DeepZang series of intelligent achievements will be deeply integrated into public services, education and medical care, cultural tourism development, grassroots governance and other scenarios. At the same time, digital technology will be relied on to protect Tibetan dialect resources, empower the digital inheritance of Tibetan excellent traditional culture, and allow people of all ethnic groups to equally share the dividends of digital technology development.
At the meeting, representatives from scientific research institutions, universities and related enterprises held in-depth discussions around the construction of ethnic language corpora, low-resource language model training, cross-language technology collaborative innovation, etc., and reached a consensus on in-depth cooperation between industry, academia and research, laying a solid foundation for subsequent joint technological research and achievement transformation.
DeepZang founder Tenzin Norbu said that the development of multi-ethnic language intelligence in my country faces similar low-resource technical problems, and cross-regional and cross-language collaborative research and development is of great significance. In the next step, the team will use this conference as an opportunity to continue to deepen the iteration and demonstration application of Tibetan AI technology, rely on scientific and technological innovation to facilitate exchanges and integration of various ethnic groups, and provide solid scientific and technological support for the digital and intelligent development of ethnic minority areas.
