# UniGlyph: A Seven-Segment Script for Universal Language Representation

arXiv: https://arxiv.org/abs/2410.08974 · HTML: https://mlsanity.com/paper/2410.08974/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 21 of its 103 references that are in the map.
- First posted on arXiv 11 Oct 2024.

## Builds on (most cited first, 21 of 21)

- [Deep Speech: Scaling up end-to-end speech recognition](https://mlsanity.com/paper/1412.5567/) (2014)
- [Deep Voice: Real-time Neural Text-to-Speech](https://mlsanity.com/paper/1702.07825/) (2017)
- [Universal Phone Recognition with a Multilingual Allophone System](https://mlsanity.com/paper/2002.11800/) (2020)
- [Sequence-to-Sequence Neural Net Models for Grapheme-to-Phoneme Conversion](https://mlsanity.com/paper/1506.00196/) (2015)
- [AmadeusGPT: a natural language interface for interactive animal behavioral analysis](https://mlsanity.com/paper/2307.04858/) (2023)
- [GPT-4o: Visual perception performance of multimodal large language models in piglet activity understanding](https://mlsanity.com/paper/2406.09781/) (2024)
- [AlloVera: A Multilingual Allophone Database](https://mlsanity.com/paper/2004.08031/) (2020)
- [From Summary to Action: Enhancing Large Language Models for Complex Tasks with Open World APIs](https://mlsanity.com/paper/2402.18157/) (2024)
- [A Theory of Unsupervised Translation Motivated by Understanding Animal Communication](https://mlsanity.com/paper/2211.11081/) (2022)
- [Large language models and (non-)linguistic recursion](https://mlsanity.com/paper/2306.07195/) (2023)
- [Visual Enumeration Remains Challenging for Multimodal Generative AI](https://mlsanity.com/paper/2402.03328/) (2024)
- [ISPA: Inter-Species Phonetic Alphabet for Transcribing Animal Sounds](https://mlsanity.com/paper/2402.03269/) (2024)
- [The Case for Animal-Friendly AI](https://mlsanity.com/paper/2403.01199/) (2024)
- [Automatic measurement of vowel duration via structured prediction](https://mlsanity.com/paper/1610.08166/) (2016)
- [Phonemic Representation and Transcription for Speech to Text Applications for Under-resourced Indigenous African Languages: The Case of Kiswahili](https://mlsanity.com/paper/2210.16537/) (2022)
- [Vocal Interactivity in Crowds, Flocks and Swarms: Implications for Voice User Interfaces](https://mlsanity.com/paper/1907.11656/) (2019)
- [Generating Novel Glyph without Human Data by Learning to Communicate](https://mlsanity.com/paper/2010.04402/) (2020)
- [Techniques and Challenges in Speech Synthesis](https://mlsanity.com/paper/1709.07552/) (2017)
- [Formal models of Structure Building in Music, Language and Animal Songs](https://mlsanity.com/paper/1901.05180/) (2019)
- [Towards Lexical Analysis of Dog Vocalizations via Online Videos](https://mlsanity.com/paper/2309.13086/) (2023)
- [Morphological Computing as Logic Underlying Cognition in Human, Animal, and Intelligent Machine](https://mlsanity.com/paper/2309.13979/) (2023)

## Abstract (arXiv)

UniGlyph is a constructed language (conlang) designed to create a universal transliteration system using a script derived from seven-segment characters. The goal of UniGlyph is to facilitate cross-language communication by offering a flexible and consistent script that can represent a wide range of phonetic sounds. This paper explores the design of UniGlyph, detailing its script structure, phonetic mapping, and transliteration rules. The system addresses imperfections in the International Phonetic Alphabet (IPA) and traditional character sets by providing a compact, versatile method to represent phonetic diversity across languages. With pitch and length markers, UniGlyph ensures accurate phonetic representation while maintaining a small character set. Applications of UniGlyph include artificial intelligence integrations, such as natural language processing and multilingual speech recognition, enhancing communication across different languages. Future expansions are discussed, including the addition of animal phonetic sounds, where unique scripts are assigned to different species, broadening the scope of UniGlyph beyond human communication. This study presents the challenges and solutions in developing such a universal script, demonstrating the potential of UniGlyph to bridge linguistic gaps in cross-language communication, educational phonetics, and AI-driven applications.