RHYTHM METRICS PREDICT RHYTHMIC DISCRIMINATION
RHYTHM METRICS PREDICT RHYTHMIC DISCRIMINATION
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节律指标可预测节律歧视
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Suzi Gage
中科院分区：
文献类型：
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作者：
Laurence White;S. Mattys;Suzi Gage
VarcoV（声乐间隔持续时间的标准差除以平均值）和%V（由声乐间隔组成的总话语持续时间的比例）等指标为长期以来关于语言之间节奏差异的概念提供了实证支持。此外，听众可以区分语言与不同的节奏度量分数纯粹的持续时间信息的基础上重新合成的单调sasasa讲话。然而，造成这种持续时间变化的一些因素，如重音分布和韵律时间，并不直接反映在节奏得分。为了更精确地测试节奏指标的预测能力，我们使用严格控制的Sasasa刺激，消除应力分布和韵律定时线索，专注于节奏指标直接量化的信息。我们表明，VarcoV和%V分数是预测听者的语言内和语言之间的歧视，即使这些高度限制的刺激。
Metrics such as VarcoV (standard deviation of vocalic interval duration divided by the mean) and %V (proportion of total utterance duration comprised of vocalic intervals) provide empirical support for long-held notions about rhythmic distinctions between languages. Furthermore, listeners can discriminate languages with distinct rhythm metric scores purely on the basis of the durational information available in resynthesized monotone sasasa speech. However, some factors contributing to this durational variation, such as stress distribution and prosodic timing, are not directly reflected in rhythm scores. To test more precisely the predictive power of rhythm metrics, we used tightly controlled sasasa stimuli, eliminating stress distribution and prosodic timing cues to focus on the information directly quantified by rhythm metrics. We show that VarcoV and %V scores are predictive of listeners’ discrimination within and between languages, even with these highly constrained stimuli.