{"title":"Menzerath-Altmann Law in Consecutive and Simultaneous Interpreting: Insights into Varied Cognitive Processes and Load","authors":"Xinlei Jiang, Yue Jiang","doi":"10.1080/09296174.2022.2027657","DOIUrl":null,"url":null,"abstract":"ABSTRACT Notwithstanding theoretical simulations of distinctive cognitive processes and load of consecutive (CI) and simultaneous interpreting (SI), quantitative linguistic inquiry into their outputs is needed for solid empirical evidence. As a fundamental law of quantitative linguistics, Menzerath–Altmann Law (MAL) mirrors the economic processing of linguistic information and complex dynamic language system. Given its extensive validation at various linguistic levels and predictive power of its parameters in register, language and authorship differentiation, MAL is worthy of being applied to interpreting studies. We endeavour to investigate whether interpreted languages follow the MAL and reveal varied cognitive load of CI versus SI, as manifested by different MAL fitting models. Results show that (1) both CI and SI outputs follow the MAL; (2) SI processing involves more diversified structural information and shows a greater tendency of shortening the clauses of a sentence with increased sentence length, than CI processing, expressed by significantly higher a and lower b in SI models than that in CI models. Our findings suggest the disparate language representations are shaped by cognitive capacity limitations and interpreting modalities, and reveal how language system dynamically re-regulates and reorganizes the linguistic information to accommodate environmental settings from the perspective of synergetic linguistics.","PeriodicalId":45514,"journal":{"name":"Journal of Quantitative Linguistics","volume":"29 1","pages":"541 - 559"},"PeriodicalIF":0.7000,"publicationDate":"2022-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Quantitative Linguistics","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1080/09296174.2022.2027657","RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT Notwithstanding theoretical simulations of distinctive cognitive processes and load of consecutive (CI) and simultaneous interpreting (SI), quantitative linguistic inquiry into their outputs is needed for solid empirical evidence. As a fundamental law of quantitative linguistics, Menzerath–Altmann Law (MAL) mirrors the economic processing of linguistic information and complex dynamic language system. Given its extensive validation at various linguistic levels and predictive power of its parameters in register, language and authorship differentiation, MAL is worthy of being applied to interpreting studies. We endeavour to investigate whether interpreted languages follow the MAL and reveal varied cognitive load of CI versus SI, as manifested by different MAL fitting models. Results show that (1) both CI and SI outputs follow the MAL; (2) SI processing involves more diversified structural information and shows a greater tendency of shortening the clauses of a sentence with increased sentence length, than CI processing, expressed by significantly higher a and lower b in SI models than that in CI models. Our findings suggest the disparate language representations are shaped by cognitive capacity limitations and interpreting modalities, and reveal how language system dynamically re-regulates and reorganizes the linguistic information to accommodate environmental settings from the perspective of synergetic linguistics.
期刊介绍:
The Journal of Quantitative Linguistics is an international forum for the publication and discussion of research on the quantitative characteristics of language and text in an exact mathematical form. This approach, which is of growing interest, opens up important and exciting theoretical perspectives, as well as solutions for a wide range of practical problems such as machine learning or statistical parsing, by introducing into linguistics the methods and models of advanced scientific disciplines such as the natural sciences, economics, and psychology.