Newest papers

Using Letter Positional Probabilities to Assess French Word Complexity

Michael Coleman Dalvean · 2026 · SSRN Electronic Journal

DOI: 10.2139/ssrn.7595722 · cited by 0 works (OpenAlex) · open-access PDF

Indonesian

Kami menggunakan Letter Positional Probabilities (LPPs) untuk memeriksa perbedaan ortografi antara kata-kata Perancis sederhana dan rumit. Kami menarik dari sampel 38.000 kata Perancis yang dicetak oleh waktu reaksi pada tugas keputusan lexikal. Kami mengambil 5000 kata waktu reaksi tertinggi dan 5.000 kata terendah sebagai proxy untuk kelompok kompleksitas kata tinggi dan rendah masing-masing. Kami membuat 18 variabel berdasarkan struktur kata-kata, seperti panjang dan jumlah huruf. Kami juga mengurangi setiap kata menjadi string nilai biner dengan mengenkripsi setiap huruf sesuai dengan 42 karakter dari alfabet Perancis standar

Machine translation (Meta M2M100); the English original follows.

Abstract

We use Letter Positional Probabilities (LPPs) to examine the orthographic differences between simple and complex French words. We draw from a sample of 38,000 French words scored by reaction time on a lexical decision task. We take the 5000 highest reaction time words and the 5000 lowest as a proxy for high and low word complexity groups respectively. We create 18 variables based on the structure of the words, such as length and number of syllables. We also reduce each word to a string of binary values by one-hot encoding each letter according to the 42 characters of the standard French alphab

Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese

Topics: Word (group theory), Binary number, Computer science, Word length, Natural language processing, String (physics)

Sources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange