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  1. The UCLA Phonological Segment Inventory Database (or UPSID) is a statistical survey of the phoneme inventories in 451 of the world's languages. The database was created by American phonetician Ian Maddieson for the University of California, Los Angeles (UCLA) in 1984 and has been updated several times.

  2. phoible.org › contributors › UPSIDPHOIBLE 2.0

    In the early 1980's, Ian Maddieson developed the UCLA Phonological Segment Inventory Database (UPSID), a computer-accessible database of contrastive segment inventories (Maddieson 1984).

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  4. UCLA Phonetics Lab Archive (raw data files not structured for teaching) (NOTE: These files have been digitized at very high sampling rates. It is often useful to downsample before acoustic analysis. See Henry for a Matlab routine to do this; or check out Praat scripts to do this.)

  5. The UCLA Phonological Segment Inventory Database. Data on the phonological systems of 451 languages, with programs to access it, by Ian Maddieson and Kristin Precoda. This is an elderly DOS program (and thus Windows only), neither of whose developers are still at UCLA, and no support is offered.

  6. This site is a (hopefully) simple user interface to the UCLA Phonological Segment Inventory Database (UPSID). This Database was compiled by Ian Maddieson and Kristin Precoda (cf. Maddieson, 1984) and contains information on the distribution of 919 different segments in 451 languages.

  7. Aug 4, 2010 · The following pages contain charts showing the phoneme inventory of each of the carefully selected sample of 317 languages which comprise the UCLA Phonological Segment Inventory Database (UPSID). It also includes an index of each segment type which occurs in the database.

  8. Aug 4, 2010 · Summary. Introduction. As remarked in the preface to this volume, the discovery of generalizations concerning the content and structure of phonological inventories has been a significant objective of recent work in linguistics. UPSID is designed as a tool for research into these questions, providing uniform data from a properly balanced sample ...