Collaborative Research: Contributions of Endangered Language Data for Advances in Technology-enhanced Speech Annotation

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Linguists have increased efforts to collect authentic speech materials from endangered and little-studied languages to discover linguistic diversity. However, the challenge of transcribing these speech into written form to facilitate analysis is daunting. This is because of both the sheer quantity of digitally collected speech that needs to be transcribed and the difficulty of unpacking the sounds of spoken speech. Linguist Andreas Kathol and computer scientist Vikramjit Mitra of SRI international and linguist Jonathan D. Amith of Gettysburg College will team up to create software that can substantially reduce the language transcription bottleneck. Using as a test case Yoloxochitl Mixtec, an endangered language from the state of Guerrero, Mexico, the team will develop a software tool that will use previously transcribed Yoloxochitl Mixtec speech data to both train a new generation of native speakers in practical orthography and to develop automatic speech recognition software. The output of the recognition software will be used as preliminary transcription that native speakers will correct, as necessary, to create additional high-quality training data. This recursive method will create corpus of transcribed speech large enough so that software will be able to complete automatic transcription of newly collected speech materials. The project will include the training of undergraduate and graduate students in software development and the analysis of the Yoloxochitl Mixtec sound system. The project will also train native speakers as documenters in an interactive fashion that systematically introduces them to the transcription conventions of their language. This software tool will help in establishing literacy in Yoloxochitl Mixtec among a broader base of speakers. The results of this project will be available at the Archive of Indigenous Languages of Latin America (University of Texas, Austin), Kaipuleohone (University of Hawai'i Digital Language Archive), and at the Linguistic Data Consortium (University of Pennsylvania).