Enabling Interactive Transcription in an Indigenous Community
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Abstract (arXiv)
We propose a novel transcription workflow which combines spoken term detection and human-in-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.
Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). First posted on arXiv 12 Nov 2020.
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Citing papers per year: 2021: 2; 2022: 2.
4 papers.
- 2021Leveraging pre-trained representations to improve access to untranscribed speech from endangered languagescited by 8
- 2022Keyword localisation in untranscribed speech using visually grounded speech modelscited by 7
- 2022Automated speech tools for helping communities process restricted-access corpora for language revival effortscited by 3
- 2021Spoken Term Detection Methods for Sparse Transcription in Very Low-resource Settingscited by 0
- 2022Automated speech tools for helping communities process restricted-access corpora for language revival efforts15 Apr 2022
- 2022Keyword localisation in untranscribed speech using visually grounded speech models2 Feb 2022
- 2021Spoken Term Detection Methods for Sparse Transcription in Very Low-resource Settings11 Jun 2021
- 2021Leveraging pre-trained representations to improve access to untranscribed speech from endangered languages26 Mar 2021