# Enabling Interactive Transcription in an Indigenous Community

arXiv: https://arxiv.org/abs/2011.06198 · HTML: https://mlsanity.com/paper/2011.06198/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Nov 2020.

## Built on by (most cited first, 4 of 4)

- [Leveraging pre-trained representations to improve access to untranscribed speech from endangered languages](https://mlsanity.com/paper/2103.14583/) (2021)
- [Keyword localisation in untranscribed speech using visually grounded speech models](https://mlsanity.com/paper/2202.01107/) (2022)
- [Automated speech tools for helping communities process restricted-access corpora for language revival efforts](https://mlsanity.com/paper/2204.07272/) (2022)
- [Spoken Term Detection Methods for Sparse Transcription in Very Low-resource Settings](https://mlsanity.com/paper/2106.06160/) (2021)

## 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.