Philip Ganchev – Comprehensive Exam – 2003 - 12 - 09
نویسندگان
چکیده
Many programs learn from data represented as feature vectors. Discuss the strengths and weaknesses of this representation for learning and the assumptions that underlie it in the context of learning. Include, but do not limit yourself to, some discussion of uncertainty, semantics, and relational learning. Focus your discussion more on the representation of the data than on the learning algorithms or the representation of learned information.
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Text-Independent Speaker Verification: The WCL-1 System
A text-independent Probabilistic Neural Network (PNN)-based speaker verification system, referred to as WCL-1, is presented. A modular structure, with a distinct PNN for each enrolled speaker, is employed. A gender-dependent universal background model is created to represent the world of possible impostor speakers. Beside portrayal of the WCL-1 system, a comprehensive description of the results...
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