Abstract: We propose a novel transcription workflow which combines spoken term detection and humanin-the-loop, together with a pilot experiment. This work is grounded in an almost zero-resource
scenario where only a few terms have so far been identified, involving two endangered languages.
We show that in the early stages of transcription, when the available data is insufficient to train
a robust ASR system, it is possible to take advantage of the transcription of a small number of
isolated words in order to bootstrap the transcription of a speech collection.
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