Literature DB >> 21476670

A study of acoustic-to-articulatory inversion of speech by analysis-by-synthesis using chain matrices and the Maeda articulatory model.

Sankaran Panchapagesan1, Abeer Alwan.   

Abstract

In this paper, a quantitative study of acoustic-to-articulatory inversion for vowel speech sounds by analysis-by-synthesis using the Maeda articulatory model is performed. For chain matrix calculation of vocal tract (VT) acoustics, the chain matrix derivatives with respect to area function are calculated and used in a quasi-Newton method for optimizing articulatory trajectories. The cost function includes a distance measure between natural and synthesized first three formants, and parameter regularization and continuity terms. Calibration of the Maeda model to two speakers, one male and one female, from the University of Wisconsin x-ray microbeam (XRMB) database, using a cost function, is discussed. Model adaptation includes scaling the overall VT and the pharyngeal region and modifying the outer VT outline using measured palate and pharyngeal traces. The inversion optimization is initialized by a fast search of an articulatory codebook, which was pruned using XRMB data to improve inversion results. Good agreement between estimated midsagittal VT outlines and measured XRMB tongue pellet positions was achieved for several vowels and diphthongs for the male speaker, with average pellet-VT outline distances around 0.15 cm, smooth articulatory trajectories, and less than 1% average error in the first three formants.

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Year:  2011        PMID: 21476670      PMCID: PMC3188964          DOI: 10.1121/1.3514544

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  8 in total

1.  Inferring articulation and recognizing gestures from acoustics with a neural network trained on x-ray microbeam data.

Authors:  G Papcun; J Hochberg; T R Thomas; F Laroche; J Zacks; S Levy
Journal:  J Acoust Soc Am       Date:  1992-08       Impact factor: 1.840

2.  Modeling the articulatory space using a hypercube codebook for acoustic-to-articulatory inversion.

Authors:  Slim Ouni; Yves Laprie
Journal:  J Acoust Soc Am       Date:  2005-07       Impact factor: 1.840

3.  Incorporation of phonetic constraints in acoustic-to-articulatory inversion.

Authors:  Blaise Potard; Yves Laprie; Slim Ouni
Journal:  J Acoust Soc Am       Date:  2008-04       Impact factor: 1.840

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Authors:  M R Schroeder
Journal:  J Acoust Soc Am       Date:  1967-04       Impact factor: 1.840

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Authors:  M M Sondhi
Journal:  J Acoust Soc Am       Date:  1974-05       Impact factor: 1.840

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Authors:  P Mermelstein
Journal:  J Acoust Soc Am       Date:  1973-04       Impact factor: 1.840

7.  Inversion of articulatory-to-acoustic transformation in the vocal tract by a computer-sorting technique.

Authors:  B S Atal; J J Chang; M V Mathews; J W Tukey
Journal:  J Acoust Soc Am       Date:  1978-05       Impact factor: 1.840

8.  Determination of the vocal-tract shape from measured formant frequencies.

Authors:  P Mermelstein
Journal:  J Acoust Soc Am       Date:  1967-05       Impact factor: 1.840

  8 in total
  3 in total

1.  Statistical Methods for Estimation of Direct and Differential Kinematics of the Vocal Tract.

Authors:  Adam Lammert; Louis Goldstein; Shrikanth Narayanan; Khalil Iskarous
Journal:  Speech Commun       Date:  2013-01       Impact factor: 2.017

2.  Pathological Voice Source Analysis System Using a Flow Waveform-Matched Biomechanical Model.

Authors:  Xiaojun Zhang; Lingling Gu; Wei Wei; Di Wu; Zhi Tao; Heming Zhao
Journal:  Appl Bionics Biomech       Date:  2018-07-02       Impact factor: 1.781

3.  Discrete constriction locations describe a comprehensive range of vocal tract shapes in the Maeda model.

Authors:  Jessica L Gaines; Kwang S Kim; Benjamin Parrell; Vikram Ramanarayanan; Srikantan S Nagarajan; John F Houde
Journal:  JASA Express Lett       Date:  2021-12-28
  3 in total

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