Description
| This course guides students to learn the techniques involved in the human-machine interaction based on speech recognition, including speech signal analysis, phoneme/syllable recognition, word recognition, continuous speech recognition, semantic recognition, speaker recognition, language recognition, speech synthesis. The theoretical fundamentals on dynamic time warping, hidden Markov model, neural network/deep learning, speaker and environment adaptation, language modeling, etc. are also introduced. In addition, the course is designed with the Problem-Based Learning (PBL) method, which includes group discussion and collaboration on working projects, corporate visit, and project presentation, etc., so that students' capabilities of creativity and innovation can be developed or enhanced.
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