The language redundancy of a syllable, measured by its predictability given its context and inherent frequency, has been shown to have a strong inverse relationship with syllabic duration. This relationship is predicted by the smooth signal redundancy hypothesis, which proposes that robust communication in a noisy environment can be achieved with an inverse relationship between language redundancy and the predictability given acoustic observations (acoustic redundancy). A general version of the hypothesis predicts similar relationships between the spectral characteristics of speech and language redundancy. However, investigating this claim is hampered by difficulties in measuring the spectral characteristics of speech within large conversational corpora, and difficulties in forming models of acoustic redundancy based on these spectral characteristics. This paper addresses these difficulties by testing the smooth signal redundancy hypothesis with a very high-quality corpus collected for speech synthesis, and presents both durational and spectral data from vowel nuclei on a vowel-by-vowel basis. Results confirm the duration/language redundancy results achieved in previous work, and show a significant relationship between language redundancy factors and the first two formants, although these results vary considerably by vowel. In general, however, vowels show increased centralization with increased language redundancy.
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As a result of the "publish or perish" environment for biomedical journal authors, as well as new developments in open access publication models ("pay to publish") and rapid improvements in artificial intelligence large language models (like ChatGPT), troubling trends and a propensity for ethical violations now exists. Credit is commonly being taken for authorship by those who fail to meet authorial criteria, which is unethical. Experienced co-authors are providing inadequate diligence in drafting, critical review, and final approval of submitted articles, which is unethical, or at the very least, careless.
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Department of Computer Science and Technology, Xinzhou Normal University, Xinzhou, China.
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National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi 214122, China.
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