Abstract

SEPULVEDA-SEPULVEDA, Alexander  and  CASTELLANOS-DOMINGUEZ, German. Time-Frequency Energy Features for Articulator Position Inference on Stop Consonants. ing.cienc. [online]. 2012, vol.8, n.16, pp.37-56. ISSN 1794-9165.

Acoustic-to-Articulatory inversion offers new perspectives and interesting applications in the speech processing field; however, it remains an open issue. This paper presents a method to estimate the distribution of the articulatory information contained in the stop consonants' acoustics, whose parametrization is achieved by using the wavelet packet transform. The main focus is on measuring the relevant acoustic information, in terms of statistical association, for the inference of the position of critical articulators involved in stop consonants production. The rank correlation Kendall coefficient is used as the relevance measure. The maps of relevant time-frequency features are calculated for the MOCHA-TIMIT database; from which, stop consonants are extracted and analysed. The proposed method obtains a set of time-frequency components closely related to articulatory phenemenon, which offers a deeper understanding into the relationship between the articulatory and acoustical phenomena. The relevant maps are tested into an acoustic-to-articulatory mapping system based on Gaussian mixture models, where it is shown they are suitable for improving the performance of such a systems over stop consonants. The method could be extended to other manner of articulation categories, e.g. fricatives, in order to adapt present method to acoustic-to-articulatory mapping systems over whole speech.

Keywords : acoustic-to-Articulatory inversion; Gaussian mixture models; articulatory phonetics; time-frequency features.

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