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In most research into lexical acquisition, the robot has no pre-existing lexical knowledge.
This paper describes how to achieve highly accurate unsupervised spatial lexical acquisition from speech-recognition results including phoneme recognition errors.
Therefore, we propose an unsupervised machine learning method (SpCoA++) for the robust lexical acquisition of novel words relating to places visited by the robot.
We are investigating the role of variables such as input word frequency and prosody in one child's lexical acquisition using the Human Speechome Project corpus.
Other experiments are included with the FrameNet data mapped into the common relation inventory developed for definition analysis, illustrating how preposition disambiguation might be applied in lexical acquisition.
In the present study, the electrophysiological underpinnings of these mechanisms are explored during the critical phase of lexical acquisition using a picture-word matching paradigm.
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Toddlers show off their latest lexical acquisitions while looking at picture books and family photos.
Our objective was to define methods for lexical knowledge acquisition that are both scalable and linguistically "appealing", that is, amenable to a theoretically founded analysis of language.
In these trees, the branches that separate the nodes are measured in units of lexical replacement (acquisition of novel words); the nodes themselves represent language-splitting events, the linguistic equivalent to a speciation event.
In this paper we describe and evaluate the results of a large-scale lexical learning system, ARIOSTO_LEX, that uses a combination of probabilistic and knowledge-based methods for the acquisition of selectional restrictions of words in sublanguages.
"Earl" is a concise, foul explosion of lexical skill.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com