首页|Researcher from Nagoya University of Commerce and Business Details New Studies and Findings in the Area of Artificial Intelligence (Using artificial intelligence to explore sound symbolic expressions of gender in American English)

Researcher from Nagoya University of Commerce and Business Details New Studies and Findings in the Area of Artificial Intelligence (Using artificial intelligence to explore sound symbolic expressions of gender in American English)

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A new study on artificial intelligence is now available. According to news reporting from Aichi, Japan, by NewsRx journalists, research stated, “This study investigates the extent to which gender can be inferred from the phonemes that make up given names and words in American English.” Funders for this research include Japanese Society For The Promotion of Science (Jsps) Kakenhi. Our news correspondents obtained a quote from the research from Nagoya University of Commerce and Business: “Two extreme gradient boosted algorithms were constructed to classify words according to gender, one using a list of the most common given names (N 1,000) in North America and the other using the Glasgow Norms (N 5,500), a corpus consisting of nouns, verbs, adjectives, and adverbs which have each been assigned a psycholinguistic score of how they are associated with male or female behaviour. Both models report significant findings, but the model constructed using given names achieves a greater accuracy despite being trained on a smaller dataset suggesting that gender is expressed more robustly in given names than in other word classes. Feature importance was examined to determine which features were contributing to the decision-making process. Feature importance scores revealed a general pattern across both models, but also show that not all word classes express gender the same way.”

Nagoya University of Commerce and BusinessAichiJapanAsiaArtificial IntelligenceEmerging TechnologiesMachine Learning

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Feb.1)
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