arXiv Computation and Language

Marking Contour Tones in Yor\`{u}b\'{a}

arXiv Computation and Language
Sep 22

Type-Driven Tokenization for Brahmic Scripts

arXiv:2609.22125v1 Announce Type: new Abstract: Standard tokenizers used in large language models produce malformed text when applied to Brahmic scripts. They are a family of abugidas, writing system...

By Sai Hemanth Kapila, Rakshika Bagavathy
arXiv Computation and Language
Sep 17

The Limits of BPE Tokenization in Polish: Segmentation-Flexional Forms, Grammatical Anchoring, and First-Person Stability in Inflectional Language Models

The article examines how Byte‑Pair Encoding (BPE) tokenization handles Polish, an inflectional language, and finds that BPE tends to stabilize frequent surface fragments of grammatical exponents rather than true grammatical categories. It introduces the concept of grammatical form anchoring, showing that certain Polish verb forms can signal the speaking subject without an explicit pronoun, and highlights that language models may lack a stable grammatical "I" and can shift gender or mirror user forms. The study proposes Roclawski’s segmentation‑flexional forms as a diagnostic framework and suggests that more stable Polish modeling would require sublexical stabilization, anchoring grammatical form in the inflectional system, and maintaining the grammatical "I" in dialogue.

By Elzbieta Dawidek (University of Lower Silesia DSW Ideis)
arXiv Computation and Language
Sep 7

MoirfEolas and Cr\'iochScore: Developing Resources for and the Evaluation of Tokenization Alignment with Irish Morphology

The paper introduces MoirfEolas, a dataset of over 35,000 Irish words annotated with their morphological components, and CríochScore, a metric that measures how well tokenization aligns with these morphological boundaries. Using CríochScore, the authors evaluate common tokenization algorithms and find that the Unigram Language Model best aligns with Irish morphology. They also discuss trade‑offs between morphological alignment, compression, and vocabulary efficiency, offering practical guidance for Irish NLP development.

By Jane Adkins, Abigail Walsh, Brian Davis, Elaine U\'i Dhonnchadha
arXiv Computation and Language
Sep 18

A Phonemically Comprehensive, ASCII-Only Romanization Scheme for Thai and Lao: Systematic Cross-Lingual Correspondence and Chinese-User-Friendly Design

The paper introduces an ASCII‑only romanization system that covers all phonemic distinctions in Thai and Lao, including segmental contrasts, vowel length, and lexical tone. It ensures one‑symbol‑one‑phoneme transparency and systematic cross‑lingual correspondence between the two languages, while also aligning with Pinyin and Jyutping where possible. The design prioritizes synchronic phonetic clarity, offers optional historical tone annotations, and results in a readable, keyboard‑friendly, machine‑processable representation useful for language learning and cross‑lingual speech processing.

By Zijie Zhang, Tan Lee
arXiv Computation and Language
Sep 7

Evaluation of Phonetic Encoding Algorithms on Transcription Datasets

The paper introduces a new evaluation framework for phonetic encoding algorithms, using a generalized Rand Index called the Hüllermeier‑Rifqi Index. It measures discordance by comparing pairwise similarity scores of ground‑truth IPA transcriptions with those of encoded strings, adjusted against a random generator. The method is applied to multilingual datasets, assessing recall via collision rate and demonstrating its use in evaluating orthographic transparency.

By Can \"Ozbey, Emre Kaplan, Berkin Deniz Kahya
arXiv AI
Jun 17

findsylls: A Language-Agnostic Toolkit for Syllable-Level Speech Tokenization and Embedding

arXiv:2603. 26292v2 Announce Type: replace-cross Abstract: Syllable-level units offer compact and linguistically meaningful representations for spoken language modeling and unsupervised word discovery, but research on syllabification remains fragmented across disparate implementations, datasets, and evaluation protocols.

By H\'ector Javier V\'azquez Mart\'inez