This course covers all relevant knowledge in automatic speech recognition and partially introduces natural language processing. Basic concepts in machine learning, e.g. Bayesian decision theory, maximum-likelihood training, pattern classification will also be covered. The most important components in speech recognition, e.g. acoustic model, language model and pronunciation dictionary will be discussed separately. Some very popular language tasks, e.g. machine translation, information extraction, text classification will also be discussed. At the end of the course, the students should know how to design a real-life application based on the components they learned.

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