Taipei, Taiwan

Yun-Nung Chen


Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2025

Loading Chart...
1 patent (USPTO):Explore Patents

Title: Innovations of Yun-Nung Chen in Semantic Frame Parsing

Introduction

Yun-Nung Chen is a prominent inventor based in Taipei, Taiwan. He has made significant contributions to the field of spoken language understanding through his innovative patent. His work focuses on enhancing the capabilities of processing units in understanding and interpreting human language.

Latest Patents

Yun-Nung Chen holds a patent for "Multi-domain joint semantic frame parsing." This invention involves a processing unit that can train a model as a joint multi-domain recurrent neural network (JRNN). The model can be a bi-directional recurrent neural network (bRNN) or a recurrent neural network with long-short term memory (RNN-LSTM). The primary application of this technology is in spoken language understanding (SLU). The trained model can jointly model slot filling, intent determination, and domain classification. This joint multi-domain model can estimate a complete semantic frame per query, enabling multi-task deep learning by leveraging data from multiple domains. The JRNN can effectively utilize semantic intents and slots across various domains.

Career Highlights

Yun-Nung Chen is currently associated with Microsoft Technology Licensing, LLC, where he continues to innovate and contribute to advancements in technology. His work has been instrumental in pushing the boundaries of what is possible in the realm of artificial intelligence and natural language processing.

Collaborations

Yun-Nung Chen collaborates with Asli Celikyilmaz, working together to enhance the capabilities of their projects and drive innovation in their field.

Conclusion

Yun-Nung Chen's contributions to semantic frame parsing and spoken language understanding highlight his role as a leading inventor in the technology sector. His innovative approaches continue to shape the future of artificial intelligence and natural language processing.

This text is generated by artificial intelligence and may not be accurate.
Please report any incorrect information to support@idiyas.com
Loading…