In this study, we address various measures that have been employed to distinguish between syllable and stress-timed languages. This study differs from all previous ones by (i) exploring and comparing multiple metrics within a quantitative and multifactorial perspective and by (ii) also documenting the impact of corpus-based word frequency. We begin with the basic distinctions of speech rhythms, dealing with the differences between syllable-timed languages and stress-timed languages and several methods that have been used to attempt to distinguish between the two. We then describe how these metrics were used in the current study comparing the speech rhythms of Mexican Spanish speakers and bilingual English/Spanish speakers (speakers born to Mexican
In this study, we address various measures that have been employed to distinguish between syllable and stress-timed languages. This study differs from all previous ones by (i) exploring and comparing multiple metrics within a quantitative and multifactorial perspective and by (ii) also documenting the impact of corpus-based word frequency. We begin with the basic distinctions of speech rhythms, dealing with the differences between syllable-timed languages and stress-timed languages and several methods that have been used to attempt to distinguish between the two. We then describe how these metrics were used in the current study comparing the speech rhythms of Mexican Spanish speakers and bilingual English/Spanish speakers (speakers born to Mexican parents in California). More specifically, we evaluate how well various metrics of vowel duration variability as well as the so far understudied factor of corpus-based frequency allow to classify speakers as monolingual or bilingual. A binary logistic regression identifies several main effects and interactions. Most importantly, our results call the utility of a particular rhythm metric, the PVI, into question and indicate that corpus data in the form of lemma frequencies interact with two metrics of durational variability, suggesting that durational variability metrics should ideally be studied in conjunction with corpus-based frequency data.
© 2001-2024 Fundación Dialnet · Todos los derechos reservados