Despite mechanisms of linguistic change to avoid it, there are some instances of morphological ambiguity in natural language, meaning transcription is not always purely deterministic. It tends towards determinism the more narrow you make the transcription (e.g. for English, annotating stress patterns will avoid some ambiguity in places; transcribing to something like narrow IPA will avoid more), and context (=the semantic one) tends to handle the rest.
That aside, trained humans can perform the task exceedingly well despite these pitfalls. The problem with the machine is it introduces its own extralinguistic issues at every level of analysis: just the necessary interaction of a phonetic model with an LLM adds a lot of slop (pun intended).
Despite mechanisms of linguistic change to avoid it, there are some instances of morphological ambiguity in natural language, meaning transcription is not always purely deterministic. It tends towards determinism the more narrow you make the transcription (e.g. for English, annotating stress patterns will avoid some ambiguity in places; transcribing to something like narrow IPA will avoid more), and context (=the semantic one) tends to handle the rest.
That aside, trained humans can perform the task exceedingly well despite these pitfalls. The problem with the machine is it introduces its own extralinguistic issues at every level of analysis: just the necessary interaction of a phonetic model with an LLM adds a lot of slop (pun intended).