Transcribing speech for primarily oral, local languages is often a joint effort involving speakers and outsiders. It is commonly motivated by externally-defined scientific goals, alongside local motivations such as language acquisition and access to heritage materials. We explore the task of ‘learning through transcription’ through the design of a system for collaborative speech annotation. We have developed a prototype to support local and remote learner-speaker interactions in remote Aboriginal communities in northern Australia. We show that situated systems design for inclusive non-expert practice is a promising new direction for working with speakers of local languages.
|Title of host publication||Proceedings of the Fifth Workshop on the Use of Computational Methods in the Study of Endangered Languages|
|Editors||Sarah Moeller, Antonios Anastasopoulos, Antti Arppe, Aditi Chaudhary, Atticus Harrigan, Josh Holden, Jordan Lachler, Alexis Palmer, Shruti Rijhwani, Lane Schwartz|
|Place of Publication||Stroudsburg, PA|
|Publisher||Association for Computational Linguistics (ACL)|
|Number of pages||10|
|Publication status||Published - May 2022|