Metrical strength in Persian poetic metres
Datos Bibliográficos
| ID | 10140465 |
|---|---|
| Autores | Mohsen Mahdavi Mazdeh (0000-0001-8194-7690, University of Arizona, autor de correspondencia) |
| Año | 2022 |
| Volumen | 59 |
| Número | 4 |
| Páginas | 795-829 |
| Fecha de publicación | 2022-12-12 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Journal of Linguistics (JOURNAL) |
| Identificadores de la revista | ISSN: 0022-2267 • E-ISSN: 1469-7742 |
| Editorial | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s0022226722000482 |
| OpenAlex | W4311122967 |
| Idioma | EN |
| Referencias citadas | 26 |
In determining the metrical structure of quantitative poetic metres, heavy (i.e. long) syllables are usually associated with metrically strong positions. In this study, examining the case of Persian metres, I argue that the metres must be treated as temporal patterns in music, where research on rhythm perception has shown that the metrical strength of an event is not directly determined by the inter-onset interval following it but sensitive to the overall arrangement of the attack points. To identify metrically strong positions, I introduce a different method based on the performance practices of participants in the poetic tradition. The strength hierarchy is then used to offer constituency trees for the metrical forms and classify them. The structures identified for metrical forms are different from those suggested in previous accounts of Persian metres, in that they allow incomplete constituents at the left edges of metres. Building upon this general framework, a set of constraints chiefly based on well-known universal rhythmic tendencies is introduced and the Persian metre inventory is accounted for as emerging from the interaction of these constraints
Aesthetics · Art · Combinatorics · Epistemology · Event (particle physics · Hierarchy · Interval (graph theory · Linguistics · Literature · Metre · Perception · Persian · Physics · Poetry · Political science · Rhythm · Set (abstract data type · Computer Science · History · Law · Mathematics · Music and Audio Processing · Neuroscience and Music Perception · Philosophy · Phonetics and Phonology Research
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| Velocidad de citación | historical |
|---|---|
| Altamente citado | No |