Information-theoretic causal inference of lexical flow
This volume seeks to infer large phylogenetic networks from phonetically encoded lexical data and contribute in this way to the historical study of language varieties. The technical step that enables progress in this case is the use of causal inference algorithms. Sample sets of words from language...
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| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
Berlin :
Language Science Press
C 2019.
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| Col·lecció: | Language variation
4 |
| Matèries: | |
| Accés en línia: | https://langsci-press.org/catalog/book/233 Accès Université d'Orléans |
| Nota: |
Description d'après la consultation, 2020-04-29 Titre provenant de l'écran-titre Language Science Press (hors Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
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| 020 | |a 9783961101436 | ||
| 041 | 0 | |a eng | |
| 100 | 1 | |a Dellert, Johannes. | |
| 245 | 1 | 0 | |a Information-theoretic causal inference of lexical flow |c Johannes Dellert. |
| 256 | |a Données textuelles | ||
| 260 | |a Berlin : |b Language Science Press. | ||
| 260 | |c C 2019. | ||
| 490 | 0 | |a Language variation |v 4 | |
| 500 | |a Description d'après la consultation, 2020-04-29 | ||
| 500 | |a Titre provenant de l'écran-titre | ||
| 500 | |a Language Science Press (hors Licence nationale) | ||
| 504 | |a Bibliographie p. 335-350. Index | ||
| 506 | |a Ressource intégralement en libre accès | ||
| 520 | |a This volume seeks to infer large phylogenetic networks from phonetically encoded lexical data and contribute in this way to the historical study of language varieties. The technical step that enables progress in this case is the use of causal inference algorithms. Sample sets of words from language varieties are preprocessed into automatically inferred cognate sets, and then modeled as information-theoretic variables based on an intuitive measure of cognate overlap. Causal inference is then applied to these variables in order to determine the existence and direction of influence among the varieties. The directed arcs in the resulting graph structures can be interpreted as reflecting the existence and directionality of lexical flow, a unified model which subsumes inheritance and borrowing as the two main ways of transmission that shape the basic lexicon of languages. A flow-based separation criterion and domain-specific directionality detection criteria are developed to make existing causal inference algorithms more robust against imperfect cognacy data, giving rise to two new algorithms. The Phylogenetic Lexical Flow Inference (PLFI) algorithm requires lexical features of proto-languages to be reconstructed in advance, but yields fully general phylogenetic networks, whereas the more complex Contact Lexical Flow Inference (CLFI) algorithm treats proto-languages as hidden common causes, and only returns hypotheses of historical contact situations between attested languages. | ||
| 538 | |a Navigateur Web | ||
| 650 | |a Linguistique |x Histoire | ||
| 856 | 4 | |q PDF |u https://langsci-press.org/catalog/book/233 | |
| 856 | 4 | |5 452349901:675557682 |u https://ezproxy.univ-orleans.fr/login?qurl=https://langsci-press.org/catalog/book/233 |z Accès Université d'Orléans | |
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