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Acoustic-articulatory mapping in vowels by locally weighted regression.

ABSTRACT: A method for mapping between simultaneously measured articulatory and acoustic data is proposed. The method uses principal components analysis on the articulatory and acoustic variables, and mapping between the domains by locally weighted linear regression, or loess [Cleveland, W. S. (1979). J. Am. Stat. Assoc. 74, 829-836]. The latter method permits local variation in the slopes of the linear regression, assuming that the function being approximated is smooth. The methodology is applied to vowels of four speakers in the Wisconsin X-ray Microbeam Speech Production Database, with formant analysis. Results are examined in terms of (1) examples of forward (articulation-to-acoustics) mappings and inverse mappings, (2) distributions of local slopes and constants, (3) examples of correlations among slopes and constants, (4) root-mean-square error, and (5) sensitivity of formant frequencies to articulatory change. It is shown that the results are qualitatively correct and that loess performs better than global regression. The forward mappings show different root-mean-square error properties than the inverse mappings indicating that this method is better suited for the forward mappings than the inverse mappings, at least for the data chosen for the current study. Some preliminary results on sensitivity of the first two formant frequencies to the two most important articulatory principal components are presented.

SUBMITTER: McGowan RS

PROVIDER: S-EPMC2771059 | biostudies-other | 2009 Oct

REPOSITORIES: biostudies-other

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Project description:PurposeNeurodegenerative motor diseases (NMDs) have devastating effects on the lives of patients and their loved ones, in part due to the impact of neurologic abnormalities on speech, which significantly limits functional communication. Clinical speech researchers have thus spent decades investigating speech features in populations suffering from NMDs. Features of impaired articulatory function are of particular interest given their detrimental impact on intelligibility, their ability to encode a variety of distinct movement disorders, and their potential as diagnostic indicators of neurodegenerative diseases. The objectives of this scoping review were to identify (1) which components of articulation (i.e. coordination, consistency, speed, precision, and repetition rate) are the most represented in the acoustic literature on NMDs; (2) which acoustic articulatory features demonstrate the most potential for detecting speech motor dysfunction in NMDs; and (3) which articulatory components are the most impaired within each NMD.MethodThis review examined literature published between 1976 and 2020. Studies were identified from six electronic databases using predefined key search terms. The first research objective was addressed using a frequency count of studies investigating each articulatory component, while the second and third objectives were addressed using meta-analyses.ResultFindings from 126 studies revealed a considerable emphasis on articulatory precision. Of the 24 features included in the meta-analyses, vowel dispersion/distance and stop gap duration exhibited the largest effects when comparing the NMD population to controls. The meta-analyses also revealed divergent patterns of articulatory performance across disease types, providing evidence of unique profiles of articulatory impairment.ConclusionThis review illustrates the current state of the literature on acoustic articulatory features in NMDs. By highlighting the areas of need within each articulatory component and disease group, this work provides a foundation on which clinical researchers, speech scientists, neurologists, and computer science engineers can develop research questions that will both broaden and deepen the understanding of articulatory impairments in NMDs.

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Acoustic-articulatory mapping in vowels by locally weighted regression.

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