Exploration of Acoustic Features for Automatic Vowel Discrimination in Spontaneous Speech
Author: Na’im R. Tyson
Publisher: The Ohio State University
Publication date: 2012
Number of pages: 261
Format / Quality: pdf
Size: 4,4MB
In an attempt to understand what acoustic/auditory feature sets motivated transcribers towards certain labeling decisions, I built machine learning models that were capable of discriminating between canonical and non-canonical vowels excised from the Buckeye Corpus. Specifically, I wanted to model when the dictionary form and the transcribed-form of a vowel would match one another. I defined the transcribed-form of a vowel as an intended production from a speaker X labeled as Y by a transcriber. With specific acoustic/auditory feature sets extracted from a vowel, a pattern recognizer was used to produce a result indicating if the transcribed-form is an example of a citation form of a vowel.
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