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Automatic Detection of Prosodic Stress in American English Discourse (2000)
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BibTeX
@TECHREPORT{Silipo00automaticdetection,
author = {Rosaria Silipo and Steven Greenberg},
title = {Automatic Detection of Prosodic Stress in American English Discourse},
institution = {},
year = {2000}
}
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Abstract
. Due to the incompletely understood nature of prosodic stress, the implementation of an automatic transcriber is very difficult on the basis of the currently available knowledge. For this reason, a number of data driven approaches are applied to a manually annotated set of files from the OGI English Stories Corpus. The goal of this analysis is twofold. First, it aims to implement an automatic detector of prosodic stress with sufficiently reliable performance. Second, the effectiveness of the acoustic features most commonly proposed in the literature is assessed. That is, the role played by duration, amplitude and fundamental frequency of syllabic nuclei is investigated. Several data-driven algorithms, such as Artificial Neural Networks (ANN), statistical decision trees and fuzzy classification techniques, and a knowledge-based heuristic algorithm are implemented for the automatic transcription of prosodic stress. As reference, two different subsets from the OGI English stories databa...
Keyphrases
prosodic stress automatic detection american english discourse fuzzy classification technique automatic detector knowledge-based heuristic algorithm different subset ogi english story several data-driven algorithm automatic transcriber automatic transcription fundamental frequency ogi english story corpus understood nature statistical decision tree artificial neural network available knowledge reliable performance acoustic feature syllabic nucleus
