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  Empirical approaches for investigating the origins of structure in speech

Little, H., Rasilo, H., van der Ham, S., & Eryılmaz, K. (in press). Empirical approaches for investigating the origins of structure in speech. Interaction studies.

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 Creators:
Little, Hannah1, 2, 3, Author           
Rasilo, Heikki2, 4, Author
van der Ham, Sabine2, Author
Eryılmaz, Kerem2, Author
Affiliations:
1Language and Cognition Department, MPI for Psycholinguistics, Max Planck Society, ou_792548              
2Artificial Intelligence Lab, Vrije Universiteit Brussel, ou_persistent22              
3Language Evolution and Interaction Scholars of Nijmegen, MPI for Psycholinguistics, Max Planck Society, ou_2344701              
4Department of Signal Processing and Acoustics, Aalto University, Otakaari 5 A, 02150 Espoo, Finland, ou_persistent22              

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Free keywords: evolution of speech; combinatorial structure; phonetic learning; artificial language experiments
 Abstract: In language evolution research, the use of computational and experimental methods to investigate the emergence of structure in language is exploding. In this review, we look exclusively at work exploring the emergence of structure in speech, on both a categorical level (what drives the emergence of an inventory of individual speech sounds), and a combinatorial level (how these individual speech sounds emerge and are reused as part of larger structures). We show that computational and experimental methods for investigating population-level processes can be effectively used to explore and measure the effects of learning, communication and transmission on the emergence of structure in speech. We also look at work on child language acquisition as a tool for generating and validating hypotheses for the emergence of speech categories. Further, we review the effects of noise, iconicity and production effects.

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Language(s): eng - English
 Dates: 2017-05-08
 Publication Status: Accepted / In Press
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 Rev. Type: Peer
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Title: Interaction studies
Source Genre: Journal
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 1569-9757
CoNE: https://pure.mpg.de/cone/journals/resource/111082654853032