One of the greatest bottlenecks in linguistic conservation has historically been manual phonetic transcription. For every 1 hour of uncatalogued field manuscript or oral text, a trained computational linguist requires between 10 to 15 hours of manual phonetic alignment and IPA annotation.
Zero-Shot Cross-Lingual Language Models
With recent advances in self-supervised text and speech representation models, artificial intelligence can now learn Universal Phonetic Structures directly from unannotated text corpora and field notes. By training on thousands of diverse global speech and written samples, these neural architectures detect rare glottal stops, clicks, and tonal variations without requiring massive localized training sets.