A cross-linguistic database of phonetic transcription systems
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Keywords

phonetic transcription
phoneme inventory databases
cross-linguistically linked data
reference catalog
dataset

How to Cite

Anderson, C., Tresoldi, T., Chacon, T., Fehn, A.-M., Walworth, M., Forkel, R., & List, J.-M. (2018). A cross-linguistic database of phonetic transcription systems. Yearbook of the Poznan Linguistic Meeting, 4(1), 21–53. https://doi.org/10.2478/yplm-2018-0002

Abstract

Contrary to what non-practitioners might expect, the systems of phonetic notation used by linguists are highly idiosyncratic. Not only do various linguistic subfields disagree on the specific symbols they use to denote the speech sounds of languages, but also in large databases of sound inventories considerable variation can be found. Inspired by recent efforts to link cross-linguistic data with help of reference catalogues (Glottolog, Concepticon) across different resources, we present initial efforts to link different phonetic notation systems to a catalogue of speech sounds. This is achieved with the help of a database accompanied by a software framework that uses a limited but easily extendable set of non-binary feature values to allow for quick and convenient registration of different transcription systems, while at the same time linking to additional datasets with restricted inventories. Linking different transcription systems enables us to conveniently translate between different phonetic transcription systems, while linking sounds to databases allows users quick access to various kinds of metadata, including feature values, statistics on phoneme inventories, and information on prosody and sound classes. In order to prove the feasibility of this enterprise, we supplement an initial version of our cross-linguistic database of phonetic transcription systems (CLTS), which currently registers five transcription systems and links to fifteen datasets, as well as a web application, which permits users to conveniently test the power of the automatic translation across transcription systems.

https://doi.org/10.2478/yplm-2018-0002
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