Lee Suchardt, Jacob2025-06-132025-06-132025-06-13https://hdl.handle.net/2077/87916Abstract We set out to develop a language-agnostic ASR model for the phonetic transcription of speech into the International Phonetic Alphabet (IPA). While NLP and Automatic- Speech-Recognition (ASR) have made immense leaps in research and quality, most of the world’s languages are still excluded from this development. In the interest of aiding documentation and linguistic work with low-resource languages, we examine the possibility of universal Speech-to-IPA (STIPA) transcription by exploring the cross-lingual transfer of STIPA knowledge, as learnt from high-resource languages, to unseen and low-resource languages in zero-shot settings. Our specific goal is the application and evaluation of cross-lingual STIPA to the severely endangered language Sanna (also ”Cypriot Maronite Arabic”, described in e.g. Borg, 2011).engmachine learning, automatic-speech-recognition, cross-lingual transfer learning, phonetic transcription, speech-to-IPA, low-resource languages, WhisperText