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Evaluation of Phonetic Encoding Algorithms on Transcription Datasets

Summary

The paper introduces a novel evaluation framework based on the Hüllermeier-Rifqi Index, a generalized variant of the Rand Index, to assess how faithfully phonetic encoding algorithms preserve the similarity structure of word-level IPA transcriptions. Pairwise similarities are computed with normalized edit distance, and a discordance score is derived from the absolute difference between ground-truth and encoded similarities, then calibrated against a random-string baseline. The authors benchmark a range of phonetic encoders on multilingual transcription datasets, supplementing the evaluation with recall analysis based on collision rates, and demonstrate the framework's value for measuring orthographic transparency.

SourcearXiv Computational LinguisticsAuthor: Can \"Ozbey, Emre Kaplan, Berkin Deniz Kahya
Evaluation of Phonetic Encoding Algorithms on Transcription Datasets
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[Submitted on 3 Sep 2026]

Title:Evaluation of Phonetic Encoding Algorithms on Transcription Datasets

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Abstract:In this work, a novel evaluation scheme built on a generalized variant of the Rand Index measure, namely, the Hüllermeier-Rifqi Index, is proposed in order to assess how well phonetic encoding algorithms conform to word-based transcriptions in IPA (International Phonetic Alphabet) notation. For this objective, the discordance score is obtained by calculating the absolute difference between the pairwise similarity values of ground-truth transcriptions and those of corresponding phonetic encodings, which are computed using normalized edit distance as a permutation dependent string metric. The resulting score is subsequently adjusted with respect to that of a random string generator incorporating the same alphabet as the encoder under consideration. A wide range of phonetic encoders were evaluated as such on multi-lingual transcription datasets along with their recall capabilities based on the collision rate. The validity of the proposed scheme is further supported by its applicability in measuring the orthographic transparency of a language when the writing system is viewed as an inherent phonetic representation.

Comments: 17 pages, 3 figures, 5 tables

Subjects:

Computation and Language (cs.CL); Information Retrieval (cs.IR)

ACM classes: I.2.7; H.3.3; I.5.3

Cite as: arXiv:2609.04391 [cs.CL]

(or arXiv:2609.04391v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2609.04391

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Berkin Deniz Kahya [view email] [v1] Thu, 3 Sep 2026 18:57:32 UTC (89 KB)

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Key points

  • Proposes a Hüllermeier-Rifqi Index-based discordance score to evaluate phonetic encoders against IPA transcriptions.
  • Uses normalized edit distance for pairwise similarity and adjusts scores with a random-string generator baseline.
  • Benchmarks multiple phonetic encoders on multilingual transcription data and examines recall via collision rates.
  • Shows the approach can also measure orthographic transparency when writing systems are viewed as phonetic representations.

Highlights and analysis are generated automatically and may contain errors. Check the original source.

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