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Computational support for early elicitation and classification of tone

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Title: Computational support for early elicitation and classification of tone
Authors: Bird, Steven
Lee, Haejoong
Issue Date: Dec 2014
Publisher: University of Hawai'i Press
Citation: Bird, Steven and Haejoong Lee. 2014. Computational support for early elicitation and classification of tone. Language Documentation & Conservation 8: 453—461
Abstract: Investigating a tone language involves careful transcription of tone on words and phrases. This is challenging when the phonological categories – the tones or melodies – have not been identified. Effects such as coarticulation, sandhi, and phrase-level prosody appear as obstacles to early elicitation and classification of tone. This article presents open source software that can assist with solving this problem. Users listen to words and phrases of interest, before grouping them into clusters having the same tonal properties. In this manner, it is possible to quickly annotate words of interest in extended recordings, and compare items that may be widely separated in the source audio to obtain consistent labelling. Users have reported that it is possible to train one’s ear to pick up on the linguistically salient distinctions. The approach is illustrated with data from Eastern Chatino (Mexico) and Alekano (Papua New Guinea). *This paper is in the series How to Study a Tone Language, edited by Steven Bird and Larry Hyman
Sponsor: National Foreign Language Resource Center
ISBN: 978-0-9856211-2-4
Rights: Creative Commons Attribution Non-Commercial Share Alike License
Appears in Collections:Volume 08 : Language Documentation & Conservation

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