Company Filing History:
Years Active: 2025
Title: Yang Zhang - Innovator in Text Normalization
Introduction
Yang Zhang is a prominent inventor based in New York, NY (US). He has made significant contributions to the field of text normalization through his innovative patent. His work focuses on enhancing the processing of textual data, which is increasingly important in today's digital landscape.
Latest Patents
Yang Zhang holds a patent for "Text normalization and inverse text normalization using weighted finite-state transducers and neural language models." This patent describes systems and methods that provide for text normalization or inverse text normalization using a hybrid language system. The approach combines rule-based processing with neural or learned processing. For instance, the hybrid method identifies semiotic tokens within textual input and generates potential plain-text conversions. These conversions are then weighted and evaluated by a trained language model, which rescues the plain-text conversion based on context to identify the highest scoring conversion for further processing within a language system pipeline. Yang's innovative approach has the potential to significantly improve text processing applications.
Career Highlights
Yang Zhang is currently employed at Nvidia Corporation, a leading technology company known for its advancements in graphics processing and artificial intelligence. His work at Nvidia allows him to leverage cutting-edge technology to further his research and development in text normalization.
Collaborations
Yang collaborates with talented individuals in his field, including Evelina Bakhturina and Boris Ginsburg. These collaborations enhance the innovative potential of his projects and contribute to the advancement of technology in text processing.
Conclusion
Yang Zhang is a notable inventor whose work in text normalization is paving the way for advancements in language processing technologies. His contributions are essential in the evolving landscape of artificial intelligence and natural language processing.