# Leveraging End-to-End ASR for Endangered Language Documentation: An Empirical Study on Yolox'ochitl Mixtec

arXiv: https://arxiv.org/abs/2101.10877 · HTML: https://mlsanity.com/paper/2101.10877/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jan 2021.

## Built on by (most cited first, 15 of 15)

- [ML-SUPERB: Multilingual Speech Universal PERformance Benchmark](https://mlsanity.com/paper/2305.10615/) (2023)
- [Towards Robust Speech Representation Learning for Thousands of Languages](https://mlsanity.com/paper/2407.00837/) (2024)
- [Not always about you: Prioritizing community needs when developing endangered language technology](https://mlsanity.com/paper/2204.05541/) (2022)
- [Combining Spectral and Self-Supervised Features for Low Resource Speech Recognition and Translation](https://mlsanity.com/paper/2204.02470/) (2022)
- [Findings of the 2023 ML-SUPERB Challenge: Pre-Training and Evaluation over More Languages and Beyond](https://mlsanity.com/paper/2310.05513/) (2023)
- [When Is TTS Augmentation Through a Pivot Language Useful?](https://mlsanity.com/paper/2207.09889/) (2022)
- [Wav2Gloss: Generating Interlinear Glossed Text from Speech](https://mlsanity.com/paper/2403.13169/) (2024)
- [Investigating data partitioning strategies for crosslinguistic low-resource ASR evaluation](https://mlsanity.com/paper/2208.12888/) (2022)
- [EURO: ESPnet Unsupervised ASR Open-source Toolkit](https://mlsanity.com/paper/2211.17196/) (2022)
- [NLP Progress in Indigenous Latin American Languages](https://mlsanity.com/paper/2404.05365/) (2024)
- [Automated speech tools for helping communities process restricted-access corpora for language revival efforts](https://mlsanity.com/paper/2204.07272/) (2022)
- [Killkan: The Automatic Speech Recognition Dataset for Kichwa with Morphosyntactic Information](https://mlsanity.com/paper/2404.15501/) (2024)
- [Breaking the Transcription Bottleneck: Fine-tuning ASR Models for Extremely Low-Resource Fieldwork Languages](https://mlsanity.com/paper/2506.17459/) (2025)
- [TalTech Systems for the Interspeech 2025 ML-SUPERB 2.0 Challenge](https://mlsanity.com/paper/2506.01458/) (2025)
- [NoLoR: An ASR-Based Framework for Expedited Endangered Language Documentation with Neo-Aramaic as a Case Study](https://mlsanity.com/paper/2412.04717/) (2024)

## Abstract (arXiv)

"Transcription bottlenecks", created by a shortage of effective human transcribers are one of the main challenges to endangered language (EL) documentation. Automatic speech recognition (ASR) has been suggested as a tool to overcome such bottlenecks. Following this suggestion, we investigated the effectiveness for EL documentation of end-to-end ASR, which unlike Hidden Markov Model ASR systems, eschews linguistic resources but is instead more dependent on large-data settings. We open source a Yolox'ochitl Mixtec EL corpus. First, we review our method in building an end-to-end ASR system in a way that would be reproducible by the ASR community. We then propose a novice transcription correction task and demonstrate how ASR systems and novice transcribers can work together to improve EL documentation. We believe this combinatory methodology would mitigate the transcription bottleneck and transcriber shortage that hinders EL documentation.