Literature DB >> 690333

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

B S Atal, J J Chang, M V Mathews, J W Tukey.   

Abstract

We present numerical methods for studying the relationship between the shape of the vocal tract and its acoustic output. For a stationary vocal tract, the articulatory-acoustic relationship can be represented as a multidimensional function of a multidimensional argument: y=f(x), where x, y are vectors describing the vocal-tract shape and the resulting acoustic output, respectively. Assuming that y may be computed for any x, we develop a procedure for inverting f(x). Inversion by computer sorting consists of computing y for many values of x and sorting the resulting (y,x) pairs into a convenient order according to y; x for a given y is then obtained by looking up y in the sorted data. Application of this method for determining parameters of an articulatory model corresponding to a given set of formant frequencies is presented. A method is also described for finding articulatory regions (fibers) which map into a single point in the acoustic space. The local nature of f(x) is determined by linearization in a small neighborhood. Larger regions are explored by extending the linear neighborhoods in small steps. This method was applied for the study of compensatory articulation. Sounds produced by various articulations along a fiber were synthesized and were compared by informal listening tests. These tests show that, in many cases of interest, a given sound could be produced by many different vocal-tract shapes.

Mesh:

Year:  1978        PMID: 690333     DOI: 10.1121/1.381848

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


  27 in total

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Journal:  J Acoust Soc Am       Date:  2010-10       Impact factor: 1.840

3.  Dynamic action units slip in speech production errors.

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4.  Vowel constrictions are recoverable from formants.

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5.  Hearing tongue loops: perceptual sensitivity to acoustic signatures of articulatory dynamics.

Authors:  Hosung Nam; Christine Mooshammer; Khalil Iskarous; D H Whalen
Journal:  J Acoust Soc Am       Date:  2013-11       Impact factor: 1.840

6.  A method for finding constrictions in high front vowels.

Authors:  Michel T-T Jackson; Richard S McGowan
Journal:  J Acoust Soc Am       Date:  2010-01       Impact factor: 1.840

7.  Perception of complete and incomplete formant transitions in vowels.

Authors:  Pierre Divenyi
Journal:  J Acoust Soc Am       Date:  2009-09       Impact factor: 1.840

8.  Variability of articulator positions and formants across nine English vowels.

Authors:  D H Whalen; Wei-Rong Chen; Mark K Tiede; Hosung Nam
Journal:  J Phon       Date:  2018-02-23

9.  Retrieving Tract Variables From Acoustics: A Comparison of Different Machine Learning Strategies.

Authors:  Vikramjit Mitra; Hosung Nam; Carol Y Espy-Wilson; Elliot Saltzman; Louis Goldstein
Journal:  IEEE J Sel Top Signal Process       Date:  2010-09-13       Impact factor: 6.856

10.  Silent Speech Recognition as an Alternative Communication Device for Persons with Laryngectomy.

Authors:  Geoffrey S Meltzner; James T Heaton; Yunbin Deng; Gianluca De Luca; Serge H Roy; Joshua C Kline
Journal:  IEEE/ACM Trans Audio Speech Lang Process       Date:  2017-11-28
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