Phone Boundary Annotation in Conversational Speech

Abstract

Phone-aligned spoken corpora are indispensable language resources for quantitative linguistic analyses and automatic speech systems. However, producing this type of data resources is not an easy task due to high costs of time and man power as well as difficulties of applying valid annotation criteria and achieving reliable inter-labeler’s consistency. Among different types of spoken corpora, conversational speech that is often filled with extreme reduction and varying pronunciation variants is particularly challenging. By adopting a combined verification procedure, we obtained reasonably good annotation results. Preliminary phone boundaries that were automatically generated by a phone aligner were provided to human labelers for verifying. Instead of making use of the visualization of acoustic cues, the labelers should solely rely on their perceptual judgments to locate a position that best separates two adjacent phones. Impressionistic judgments in cases of reduction and segment deletion were helpful and necessary, as they balanced subtle nuance caused by differences in perception.

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