台中分校搶先首發！經理人週末研修班透過一系列循序漸進課程，帶領學員由淺入深掌握 AI 理論與實務應用，您可選擇連續 8 周的經理人週末研修班完整課程，也可配合時間或原有知識選修課程，讓學習更有彈性。
➤ 關於 AI 進階理論（選修3-台中分校經理人週末研修班）
台灣產業到底有多少人已經開始引入AI的技術了呢？要實踐產業AI化的路途中，從盤點資源及資料品質，以及適合的 IT 基礎建設，並且找到合適的使力點推動，每個實踐者都會遇到不同的問題及挑戰。這系列的課程，我們邀請到不同產業的實踐家，來和大家分享什麼才是企業導入人工智慧前的關鍵。
課程時間：2020/08/28 至 2020/09/05 止，共 2 週；每週五、六早上九點到下午五點
上課人數：為維護教學品質，每班人數以 60 人為限
Dr. Yu Tsao received the Ph.D. degree in Electrical and Computer Engineering from Georgia Institute of Technology, GA, USA, in 2008. The topic of his Ph.D. research is on characterizing unknown environments for enhancing automatic speech recognition (ASR) robustness under adverse conditions. In the summers of 2004, 2005, and 2006, Dr. Tsao was with Speech Technologies Laboratory, Texas Instruments Incorporated (TI), as a summer research associate, where he was deriving algorithms to reduce online computation for ASR on mobile devices. A US patent was applied based on his research work in TI. In addition to the patent application, Dr. Tsao received a TILU (Texas Instruments Leadership University) fellowship and two conference grants offered by ISCA (International Speech Communication Association). From April 2009 to September 2011, Dr. Tsao was an expert researcher at Spoken Language Communication (SLC) Group, National Institute of Information and Communications Technology (NICT), Kyoto, Japan, where he engaged in research and product development in ASR for multi-lingual speech-to-speech translation. Several papers were published, and a Japan Patent was filed based on his research achievements. Currently, Dr. Tsao is an associate research fellow of the Research Center for Information Technology Innovation (CITI) at Academia Sinica. His recent research interests include feature compensation and model adaptation for robust speech recognition, speaker and language recognition, audio event detection, speech enhancement, voice conversion, and text to speech.
Chen was born in Taipei, Taiwan. She earned a Ph.D. degree in the Language Technologies Institute (LTI) of School of Computer Science (SCS) at Carnegie Mellon University (CMU) in 2015. Chen also holds an M.S. degree in Language Technologies from CMU SCS, and B.S. and M.S. degrees in Computer Science & Information Engineering (CSIE) from National Taiwan University (NTU).
Chen's research interests mainly focus on spoken language understanding, machine intelligence, spoken dialogue system, multimodal application, natural language processing, and deep learning. She fortunately received Best Student Paper Awards at IEEE ASRU 2013 and IEEE SLT 2010, a Best Student Paper Shortlist at ISCA INTERSPEECH 2012, and the Distinguished Master Thesis Award from ACLCLP.