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oai:www.ideals.illinois.edu:2142/82652 2023-07-11 col_2142_5131 col_2142_13736 com_2142_5130 com_2142_8975 com_2142_8903

Richard Sproat Alm, Ebba Cecilia Ovesdotter 2015-09-25T20:50:54Z 2015-09-25T20:50:54Z 10000-01-01 2008 2008 After the introduction, followed by a survey of several areas of related work in Chapter 2, Chapter 3 presents a newly developed sentence-annotated corpus resource divided into three parts for large-scale exploration of affect in texts (specifically tales). Besides covering annotation and data set description, the chapter includes a hierarchical affect model and a qualitative-interpretive examination suggesting characteristics of a subset of the data marked by high agreement in affective label assignments. Chapter 4 is devoted to experimental work on automatic affect prediction in text. Different computational methods are explored based on the labeled data set and affect hierarchy outlined in the previous chapter, with an emphasis on supervised machine learning whose results seem particularly interesting when including true affect history in the feature set. Moreover, besides contrasting classification accuracy of methods in isolation, methods' predictions are combined with weighting approaches into a joint prediction. In addition, classification with the high agreement data is specifically explored, and the impact of access to knowledge about previous affect history is contrasted empirically. Chapter 5 moves on to discuss emotion in speech. It applies interactive evolutionary computation to evolve fundamental parameters of emotional prosody in perceptual experiments with human listeners, indicating both emotion-specific trends and types of variations, and implications at the local word-level. Chapter 6 provides suggestions for continued work in related and novel areas. A concluding chapter summarizes the dissertation and its contributions. Made available in DSpace on 2015-09-25T20:50:54Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3314719.pdf: 2838051 bytes, checksum: 1195f90e0a9d420251b827a6905be8a3 (MD5) Previous issue date: 2008 Embargo set by: Seth Robbins for item 83933 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 119 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008. http://hdl.handle.net/2142/82652 (MiAaPQ)AAI3314719 eng Language, Linguistics Affect in *Text and Speech text Linguistics Linguistics University of Illinois at Urbana-Champaign Dissertation Ph.D.