Using AI to help Preserve Indigenous Oral Histories

The preservation of Indigenous oral histories is crucial for maintaining cultural heritage. This paper explores the use of artificial intelligence (AI) to enhance the accessibility and accuracy of oral history recordings. By implementing AI-driven tools for speech segmentation, transcription, and translation, we aim to support the documentation and revitalization of endangered Indigenous languages. Our focus includes developing automatic speech recognition (ASR) systems for the Enlhet language and it will be applicable to other indigenous languages. This interdisciplinary approach fosters collaboration between technical experts and Indigenous communities, ensuring the cultural and linguistic knowledge is preserved for future generations.

Authors

Institutions

Publication Details

Published
2024-11-27
DOI
https://doi.org/10.1109/ihtc61819.2024.10855026
Citations
2
Primary Topic
Diverse Musicological Studies
Type
article
Field-Weighted Citation Impact
10.42
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using AI to help Preserve Indigenous Oral Histories

Gerhard W. Dueck
2 citations
Diverse Musicological Studies
10.42
article

Using AI to help Preserve Indigenous Oral Histories

Gerhard W. Dueck
article en
2 citations

Abstract

The preservation of Indigenous oral histories is crucial for maintaining cultural heritage. This paper explores the use of artificial intelligence (AI) to enhance the accessibility and accuracy of oral history recordings. By implementing AI-driven tools for speech segmentation, transcription, and translation, we aim to support the documentation and revitalization of endangered Indigenous languages. Our focus includes developing automatic speech recognition (ASR) systems for the Enlhet language and it will be applicable to other indigenous languages. This interdisciplinary approach fosters collaboration between technical experts and Indigenous communities, ensuring the cultural and linguistic knowledge is preserved for future generations.

University of New Brunswick (CA)
Openalex Percentile: Top 2%
Diverse Musicological Studies
10.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.