Words like "face” have many meanings. A new study tracks and replicates their cognitive evolution.
What are voice-controlled personal assistants like Alexa and Siri to do when faced with words like "face” that have multiple meanings ranging from a body part to an action?. Scientists from UC Berkeley, the University of Toronto and Lehigh University in Pennsylvania have begun to identify the algorithms humans have used over the last thousand years to give words new meanings. Their findings, published this month in the online issue of the Proceedings of the National Academy of Sciences , provide new insights into how language evolves, and could help digital assistants step up their game in natural language processing. Researchers examined over 1,000 years of English language evolution and created computational models to track how words have grown new meanings over time. Their discovery has the potential to teach machines to follow the cognitive steps that humans have taken to add new definitions to their lexicon. For the study, researchers tested their computational models' ability to predict the order in which new meanings of English words have emerged over the centuries. They then checked these predictions against the Historical Thesaurus of English, which documents the dates in which English word meanings first entered the language.
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