  A major consideration in multilingual language modeling is how to best
represent languages with diverse vocabularies and scripts. Although
contemporary text encoding methods cover most of the world's writing systems,
they exhibit bias towards the high-resource languages of the Global West. As a
result, texts of underrepresented languages tend to be segmented into long
sequences of linguistically meaningless units. To address the disparities, we
introduce a new paradigm that encodes the same information with segments of
consistent size across diverse languages. Our encoding convention (MYTE) is
based on morphemes, as their inventories are more balanced across languages
than characters, which are used in previous methods. We show that MYTE produces
shorter encodings for all 99 analyzed languages, with the most notable
improvements for non-European languages and non-Latin scripts. This, in turn,
improves multilingual LM performance and diminishes the perplexity gap
throughout diverse languages.
