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3 results for “phonetic alignment”
CLDF dataset derived from List and Prokić's "Benchmark Database of Phonetic Alignments" from 2014
<p>Cite the source of the dataset as:</p> <blockquote> <p>List, Johann-Mattis and Jelena Prokić. (2014). A benchmark database of phonetic alignments in historical linguistics and dialectology. In: Proceedings of the International Conference on Language Resources and Evaluation (LREC), 26 — 31 May 2014, Reykjavik. 288-294.</p> </blockquote>
Benchmark Database for Phonetic Alignments
<p>In the last two decades, alignment analyses have become an important technique in quantitative historical linguistics and dialectology. Phonetic alignment plays a crucial role in the identification of regular sound correspondences and deeper genealogical relations between and within languages and language families. Surprisingly, up to today, there are no easily accessible benchmark data sets for phonetic alignment analyses. Here we present a publicly available database of manually edited phonetic alignments which can serve as a platform for testing and improving the performance of automatic alignment algorithms. The database consists of a great variety of alignments drawn from a large number of different sources. The data is arranged in a such way that typical problems encountered in phonetic alignment analyses (metathesis, diversity of phonetic sequences) are represented and can be directly tested.</p>
Improving phonetic alignment by handling secondary sequence structures
<p>Supplementary material accompanying the paper "Improving phonetic alignment by handling secondary sequence structures".</p> <p>The data consists of 5 files:</p> <ul> <li>gold_standard.psa : the gold standard used in the analysis in PSA format</li> <li> sca-secondary.psa : the output of the algorithm with the secondary extension</li> <li>sca-traditional.psa : the output of the traditional algorithm</li> <li>sca-secondary-diff.psa : the differences of the secondary extension compared to the GS</li> <li>sca-traditional-diff.psa : the differences of the traditional algorithm compared to the GS</li> </ul> <p>For a description of the file-format used in this dataset, please refer to the LingPy tutorial under http://lingpy.org.</p>
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