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Related Concept Videos

Language and Cognition01:27

Language and Cognition

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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Evaluating language environment analysis system performance for Chinese: a pilot study in Shanghai.

Jill Gilkerson, Yiwen Zhang, Dongxin Xu

    Journal of Speech, Language, and Hearing Research : JSLHR
    |January 24, 2015
    PubMed
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    This summary is machine-generated.

    The Language Environment Analysis (LENA) system shows promising accuracy for analyzing Mandarin and Shanghai dialect speech in children. This automated tool offers reliable word and conversational turn counts for cross-linguistic language research.

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    Area of Science:

    • Computational Linguistics
    • Developmental Psychology
    • Speech-Language Pathology

    Background:

    • Automated language analysis systems like Language Environment Analysis (LENA) are valuable tools for studying child language development.
    • Validation of these systems in diverse linguistic contexts is crucial for expanding their applicability.
    • Previous research has established LENA's efficacy in English-speaking populations.

    Purpose of the Study:

    • To assess the performance and accuracy of the LENA system for the Chinese Shanghai dialect and Mandarin (SDM) languages.
    • To compare LENA's automated analysis with human rater-based counts for SDM speech.
    • To determine the influence of child age on LENA's performance in this linguistic context.

    Main Methods:

    • 22 families with children aged 3-23 months in Shanghai participated, providing daylong audio recordings via LENA.
    • A native speaker manually reviewed 15-minute audio samples per family to identify speakers and count SDM words.
    • LENA's automated segment labeling and word counts were compared against the rater-based annotations.

    Main Results:

    • LENA exhibited good sensitivity in identifying adult and child speakers, comparable to American English validation.
    • Precision was high for adult speech but lower for child speech.
    • LENA's adult word counts showed strong correlation with rater-based Chinese character and SDM word counts.
    • LENA conversational turn counts correlated well with rater data after removing outliers, with performance varying by child age.

    Conclusions:

    • LENA provides reasonably accurate estimates of adult word count and conversational turns in SDM for the tested age range.
    • The study highlights theoretical and practical considerations for using LENA with non-English languages.
    • These promising results suggest LENA's potential for broader cross-linguistic language acquisition research.