2017/09/22 (五) 14:20 李宏毅 教授（ 台灣大學 電機系）Towards Machine Comprehension of Spoken Content
Topic：Towards Machine Comprehension of Spoken Content
Date&Time：2017/09/22 (五) 14:20
Speaker：李宏毅 教授（ 台灣大學 電機系）
Location：清華大學台達館 DELTA @R216
Bio:
Hung-yi Lee received the M.S. and Ph.D. degrees from National Taiwan University (NTU), Taipei, Taiwan, in 2010 and 2012, respectively. From September 2012 to August 2013, he was a postdoctoral fellow in Research Center for Information Technology Innovation, Academia Sinica. From September 2013 to July 2014, he was a visiting scientist at the Spoken Language Systems Group of MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). He is currently an assistant professor of the Department of Electrical Engineering of National Taiwan University, with a joint appointment at the Department of Computer Science & Information Engineering of the university. His research focuses on machine learning (especially deep learning), spoken language understanding and speech recognition.
Abstract:
With the popularity of shared videos, social networks, online courses, etc, the quantity of multimedia or spoken content is growing much faster beyond what human beings can view or listen to. Accessing large collections of multimedia or spoken content is difficult and time-consuming for humans. Hence, it will be great if the machine can listen to and understand the spoken content, and extract and visualize the key information for humans. In this talk, I will share the research about spoken content retrieval, speech summarization and speech question answering. Finally, this talk will share the research directions of machine comprehension of spoken content without speech recognition.
Date&Time：2017/09/22 (五) 14:20
Speaker：李宏毅 教授（ 台灣大學 電機系）
Location：清華大學台達館 DELTA @R216
Bio:
Hung-yi Lee received the M.S. and Ph.D. degrees from National Taiwan University (NTU), Taipei, Taiwan, in 2010 and 2012, respectively. From September 2012 to August 2013, he was a postdoctoral fellow in Research Center for Information Technology Innovation, Academia Sinica. From September 2013 to July 2014, he was a visiting scientist at the Spoken Language Systems Group of MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). He is currently an assistant professor of the Department of Electrical Engineering of National Taiwan University, with a joint appointment at the Department of Computer Science & Information Engineering of the university. His research focuses on machine learning (especially deep learning), spoken language understanding and speech recognition.
Abstract:
With the popularity of shared videos, social networks, online courses, etc, the quantity of multimedia or spoken content is growing much faster beyond what human beings can view or listen to. Accessing large collections of multimedia or spoken content is difficult and time-consuming for humans. Hence, it will be great if the machine can listen to and understand the spoken content, and extract and visualize the key information for humans. In this talk, I will share the research about spoken content retrieval, speech summarization and speech question answering. Finally, this talk will share the research directions of machine comprehension of spoken content without speech recognition.