The Internal Structure of Temporal Cost in Multilingual Neural TTS Localization

Multilingual neural text-to-speech (TTS) localization is often planned from an English source as though output duration were a single, neutral quantity. This study tests a different view: total synthesized duration is an outcome of articulation time and pause time, and their configuration may vary by language. Two essays by the same author were localized into thirteen languages and synthesized under fixed language-specific voice and rate settings, producing 26 audio files. Cross-essay duration growth was predicted with high accuracy by growth in non-space character count (R² = 0.9869; leave-one-language-out mean absolute error = 0.0260 ratio units), whereas sentence count was markedly weaker. Within-language temporal coefficients changed by a median of 1.75%, while coefficients differed substantially between language-writing-system combinations (coefficient of variation 53.12%). Acoustic decomposition at three silence thresholds revealed distinct internal patterns, including proportional stability, dynamic compensation, mixed configuration, and strong reconfiguration. Equal or predictable total durations may therefore conceal different temporal mechanisms. These mechanisms are proposed as candidate operational variables for duration planning, synchronization, quality assurance, regeneration, and future localization-cost estimation. Monetary and labor costs were not directly measured. This is an independent, non-peer-reviewed research paper.