We have always had such a vision. We hope that the machine can accurately understand what we are saying and talk to us in a smooth and natural way. Therefore, Natural Language Processing (NLP) has become one of the important branches of the field of artificial intelligence.
Perhaps everyone has heard that Chinese is one of the most difficult languages ​​to master in the world. As a human being, in the face of complex Chinese vocabulary, it is difficult for us to understand and master it accurately and quickly. This is even more true for machines. Therefore, as an important problem in the application of NLP in the Chinese environment, solving the problem of Chinese word segmentation has become the key to machine learning to understand Chinese.
So, what is the problem with Chinese word segmentation? What are the methods? How to apply? What kind of limitations and development opportunities does he have? In order to discuss these issues, we invited the inquirer engineers Dr. Xu and Jason to give us an explanation of “teaching robots to learn Chinese: parsing Chinese word segmentation and its applicationsâ€.
Guest Profile
Dr Xu
Dr. Johns Hopkins University's Speech and Speech Lab Ph.D. joined the Microsoft headquarters after graduating in 2012. He has engaged in natural language processing and machine learning related research and product development at the Bing and Microsoft Research Institutes. Cortana Semantics Understanding and Dialogue Systems team and wordflow input. The main member of the law team
Jason
He graduated from the Natural Language Processing Group at Cambridge University and has been engaged in the research and development of natural language processing. Joining the door for more than three years and asked to develop the semantic analysis system and dialogue system for outbound questions. The participating products include the mobile phone version, Ticwear intelligent voice watch interactive system, and the magical little smart customer service dialogue system.
Event Details:
Time: Wednesday, August 17, 2016, 10 am
Participation methods: Scan the poster QR code, pay attention to the public registration
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