After completing this course, the student can:
apply some of the NLP techniques for speech processing, in particular:
• Apply existing tools for speech processing (e.g. speech recognition or emotion tracking), evaluate and analyse the performance, and specify possible adaptations.
• Study existing real-life applications that use speech processing to enable user to engage with audiovisual content; evaluate the performance of the speech processing algorithms and of the functionalities;
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This course is a follow-up of Speech and Language Processing 1 (192166310) and offers a more in-depth introduction to the automatic processing of spoken language and its application in the domain of ICT. Several methods of speech processing will be discussed, plus the feasibility of their applicability within e.g., man-machine interaction and information retrieval. Several examples of running systems will be presented in more detail, partly via practical assignments. In the lectures, the following subjects will be discussed:
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Human Speech Processing
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Signal Processing
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Speech Applications
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Speech Generation
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Speech Recognition
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Dialogue and Conversational Agents
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Social Signal Processing and Speech
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Speech Retrieval
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