The task of creating speech corpora for phonetic research is time-consuming and could be alleviated by automatic algorithms to provide draft indexing of speech acts. The present investigation assessed the feasibility of applying speech segmentation and speaker diarization models across a collection of recordings to produce a draft indexing that could be utilised by speech management systems to help the researcher to navigate a corpus. The results show that a readily available model for speech segmentation is very likely to contribute to the effectiveness of speech annotation workflows in phonetic research. Speaker diarization models may require specific training to manage consistent speaker separation across a speech corpus, and the evaluated model currently offers no clear advantage to the effectiveness of a speech corpus creation process.