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根据选定的生理指标预测嗓音频率。

Predicting vocal frequency from selected physiologic measures.

作者信息

Shipp T, Doherty E T, Morrissey P

出版信息

J Acoust Soc Am. 1979 Sep;66(3):678-84. doi: 10.1121/1.383694.

DOI:10.1121/1.383694
PMID:489840
Abstract

Simultaneous physiologic measures were obtained on four young adult male subjects as they sustained phonation at seven frequencies within their modal-to-falsetto voice range. Data were analyzed using a multiple regression program to determine the contribution of each measure singly and in combination with other measures to the prediction of the resultant voice frequency. Results showed that by far the best predictor was cricothyroid muscle activity for both the pooled data model, and for each individual subject. The contribution of subglottal air pressure and thyroarytenoid muscle activity increased the variance explained by only 4% while the measure of vertical laryngeal position was a significant factor in only one subject's predictive model. Partial models from the pooled data explained from 67% to 73% of the variance; whereas the obtained measures for individual subjects explained from 90% to 94% of the variance.

摘要

对四名年轻成年男性受试者在其正常发声至假声范围内的七个频率上持续发声时进行了同步生理测量。使用多元回归程序对数据进行分析,以确定每种测量单独以及与其他测量相结合时对预测最终语音频率的贡献。结果表明,到目前为止,无论是汇总数据模型还是每个个体受试者,最佳预测指标都是环甲肌活动。声门下气压和甲杓肌活动的贡献仅使可解释的方差增加了4%,而垂直喉位测量仅在一名受试者的预测模型中是一个重要因素。汇总数据的部分模型解释了67%至73%的方差;而个体受试者的测量结果解释了90%至94%的方差。

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