LINGUISTIC MODELLING OF LOANWORDS IN UZBEK TEXT-TO-SPEECH SYSTEMS (Eureka Journal of Language, Culture & Social Change, 2026)
This paper discusses how loanwords in Uzbek – especially Russian/international and Arabic – Persian strata – should be handled in the linguistic front-end of text-to-speech (TTS) systems, using evidence from the Uzbek electronic corpus. The study aims to identify and systematize orthography – pronunciation mismatches that cause typical synthesis errors: bi-phonemic graphemes (the Uzbek letter encoding both affricate and fricative realizations), homography driven by the lack of distinct letters for foreign phonemes (e.g., the letter in certain borrowed forms), vowel sequences in loanwords that are realized with inserted glides (y/v), and stress- and syllable-structure-dependent variants. The methodology is based on descriptive analysis, phonetic – morphological interpretation, identification and analysis of typical word combinations in the electronic corpus, as well as a comparative approach to practical experiences in Turkish, Kazakh, and Tatar languages. The results propose a set of practical front-end strategies: enriched pronunciation lexicon for loanwords, context-based homograph disambiguation, explicit glide-insertion rules for vowel sequences, and curated exception lists for fricative-j items. Overall, corpus-driven linguistic normalization is argued to be the key factor for improving naturalness and reducing errors in Uzbek TTS.
Keywords: Uzbek electronic corpus, loanwords, homograph, bi-phonemic grapheme, pronunciation variant, vowel sequence, morphophonology, linguistic front-end, text-to-speech (TTS).