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Incorporating nonverbal features into multimodal models of human-to-human communication
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In: Theses and Dissertations Available from ProQuest (2008)
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Structural event detection for rich transcription of speech
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In: Theses and Dissertations Available from ProQuest (2004)
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The Effect of Pruning and Compression on Graphical Representations of the Output of a Speech Recognizer
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In: Electrical and Computer Engineering Faculty Research and Publications (2003)
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Statistical parsing and language modeling based on constraint dependency grammar
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In: Theses and Dissertations Available from ProQuest (2003)
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Investigating Probabilistic Constraint Dependency Grammars in Language Modeling
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In: Department of Electrical and Computer Engineering Technical Reports (2001)
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Abstract:
This technical report concerns the development of a probabilistic Constraint Dependency Grammar (CDG) language model for speech recognition tasks. We have developed methods to quickly annotate a medium-sized carpus of sentences and extract high quality CDGs. We have also evaluated the quality of these grammars. Using the corpus of CDG parses, we have constructed and evaluated a language model that incorporates syntactically a.nd semantically enriched Part-of-Speech (POS) tags. The N-gram language model based on the enriched tags improves the perplexity and word error rate on the test corpus compared to a standard word-based N-gram language model and an N-gram POS-based language model on our corpus. Future work focuses on developing a probabilistic CDG language model that incrementally builds up a hidden dependency parse structure that uses syntactic and lexical constraints. Partial parse information will be used as the history of a word to enable the use of long-distance dependency information for word prediction. The model will tightly integrate tagging with parsing, and utilize dependency constraints, subcategorization/expect;ztion constraints, and lexical features of words to generate parse structures. The rriodel will search the parse space in a left-bright bottom-up mannter so that it can be integrated directly with a speech recognizer. Additionally, distance measure and punctuation information will be investigated to refine the modeling of dependency structures.
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Keyword:
Constraint Dependency Grammar; Grammar Induction; Language Modeling; Statistical Parsing
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URL: https://docs.lib.purdue.edu/ecetr/12 https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1011&context=ecetr
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10 |
Familiarity and Pronounceability of Nouns and Names
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In: Electrical and Computer Engineering Faculty Research and Publications (1999)
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Parsing and tagging sentences containing lexically ambiguous and unknown tokens
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In: Theses and Dissertations Available from ProQuest (1999)
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Prosodic disambiguation in automatic speech understanding of Thai
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In: Theses and Dissertations Available from ProQuest (1995)
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Improving hidden Markov models for speech recognition
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In: Theses and Dissertations Available from ProQuest (1995)
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PARSEC: A Constraint-Based Parser for Spoken Language Processing
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In: Department of Electrical and Computer Engineering Technical Reports (1993)
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