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» Introducing Speech and Language Processing
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HRI
2010
ACM
15 years 4 months ago
Robust spoken instruction understanding for HRI
—Natural human-robot interaction requires different and more robust models of language understanding (NLU) than non-embodied NLU systems. In particular, architectures are require...
Rehj Cantrell, Matthias Scheutz, Paul W. Schermerh...
EACL
2003
ACL Anthology
14 years 11 months ago
Learning to Identify Fragmented Words in Spoken Discourse
Disfluent speech adds to the difficulty of processing spoken language utterances. In this paper we concentrate on identifying one disfluency phenomenon: fragmented words. Our d...
Piroska Lendvai
IJCSA
2008
137views more  IJCSA 2008»
14 years 9 months ago
Algorithms to Improve Performance of Natural Language Interface
: Performance of Natural Language Interface often deteriorates due to linguistic phenomena of Semantic Symmetry and Ambiguous Modification (Katz and Lin, 2003). In this paper we pr...
M. R. Joshi, R. A. Akerkar
SPEECH
2010
89views more  SPEECH 2010»
14 years 4 months ago
Which words are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates
Despite years of speech recognition research, little is known about which words tend to be misrecognized and why. Previous work has shown that errors increase for infrequent words...
Sharon Goldwater, Daniel Jurafsky, Christopher D. ...
ACL
2007
14 years 11 months ago
Unsupervised Language Model Adaptation Incorporating Named Entity Information
Language model (LM) adaptation is important for both speech and language processing. It is often achieved by combining a generic LM with a topic-specific model that is more releva...
Feifan Liu, Yang Liu