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  Capturing fine-phonetic variation in speech through automatic classification of articulatory features

Scharenborg, O., Wan, V., & Moore, R. K. (2006). Capturing fine-phonetic variation in speech through automatic classification of articulatory features. In Speech Recognition and Intrinsic Variation Workshop [SRIV2006] (pp. 77-82). ISCA Archive.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0012-D22C-5 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0012-D22D-3
Genre: Conference Paper

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 Creators:
Scharenborg, Odette1, Author
Wan, V.1, Author
Moore, R. K.1, Author
Affiliations:
1Speech and Hearing Research Group, Department of Computer Science, University of Sheffield, Sheffield, UK, ou_persistent22              

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 Abstract: The ultimate goal of our research is to develop a computational model of human speech recognition that is able to capture the effects of fine-grained acoustic variation on speech recognition behaviour. As part of this work we are investigating automatic feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. In the experiments reported here, we compared support vector machines (SVMs) with multilayer perceptrons (MLPs). MLPs have been widely (and rather successfully) used for the task of multi-value articulatory feature classification, while (to the best of our knowledge) SVMs have not. This paper compares the performances of the two classifiers and analyses the results in order to better understand the articulatory representations. It was found that the MLPs outperformed the SVMs, but it is concluded that both classifiers exhibit similar behaviour in terms of patterns of errors.

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Language(s): eng - English
 Dates: 2006
 Publication Status: Issued
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Title: Speech Recognition and Intrinsic Variation [SRIV2006]
Place of Event: Toulouse, France
Start-/End Date: 2006-05-20

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Title: Speech Recognition and Intrinsic Variation Workshop [SRIV2006]
Source Genre: Proceedings
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Publ. Info: ISCA Archive
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 77 - 82 Identifier: URI: http://www.isca-speech.org/archive_open/sriv2006