A Novel Approach to the Phonetic Representativeness of Writing Systems: Phonetic Correspondence Efficiency (PCE)

The phonetic representativeness of writing systems is of critical importance for the advancement of language technologies. In this study, the Phonetic Correspondence Efficiency metric is introduced to measure how accurately, uniquely, and economically a writing system captures the sound structure of a language. To evaluate the metric’s validity and practical utility, comparative analyses were conducted using datasets updated in accordance with the Common Turkic Alphabet; the results demonstrate that these updates effectively reflect improvements and changes in orthography–pronunciation alignment. Improvements of 18-19% were observed with weighted computation methods, while logarithmic approaches yielded enhancements of 11-12%. Additionally, segment-based computations indicate that the method maintains consistent performance across different scales. As PCE does not require training data or pre-trained models, it stands out as an innovative metric for assessing the overall phonetic alignment of writing systems from a universal perspective, offering significant potential for writing reforms and the development of natural language processing applications.