Determination of vocal tract shape for vowels

Сорокин, В. Н.

doi:10.1016/0167-6393(92)90064-e

Cited by 18 publications

(10 citation statements)

References 9 publications

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“…The vocal-tract shape is difficult to derive from the speech signal [1], [2]. Therefore, we use the formant parameters, which are commonly used in speech analysis and synthesis, to characterize the vocal-tract system.…”

Section: Introductionmentioning

confidence: 99%

Extraction of vocal-tract system characteristics from speech signals

Yegnanarayana

Veldhuis²

1998

IEEE Trans. Speech Audio Process.

120

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Abstract-We propose methods to track natural variations in the characteristics of the vocal-tract system from speech signals. We are especially interested in the cases where these characteristics vary over time, as happens in dynamic sounds such as consonant-vowel transitions. We show that the selection of appropriate analysis segments is crucial in these methods, and we propose a selection based on estimated instants of significant excitation. These instants are obtained by a method based on the average group-delay property of minimum-phase signals. In voiced speech, they correspond to the instants of glottal closure. The vocal-tract system is characterized by its formant parameters, which are extracted from the analysis segments. Because the segments are always at the same relative position in each pitch period, in voiced speech the extracted formants are consistent across successive pitch periods. We demonstrate the results of the analysis for several difficult cases of speech signals.

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Section: Introductionmentioning

confidence: 99%

Extraction of vocal-tract system characteristics from speech signals

Yegnanarayana

Veldhuis²

1998

IEEE Trans. Speech Audio Process.

120

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“…The technique is based on perturbing the shape of an initial vocal tract configuration with a summation of scaled acoustic sensitivity functions, such that the formants are systematically displaced toward desired values. Although it is well known that transformation of a set of formant frequencies to a vocal tract area function does not produce a unique solution ͑e.g., Schroeder, 1967;Mermelstein, 1967;Wakita, 1973;Atal, Chang, Mathews, and Tukey, 1978;Milenkovic, 1984;Sondhi and Resnick, 1983;Sorokin, 1992͒, the technique described may be useful for generating subtle, hypothetical, modifications to a specific vocal tract shape.…”

Section: Introductionmentioning

confidence: 97%

Technique for “tuning” vocal tract area functions based on acoustic sensitivity functions

Story

2006

The Journal of the Acoustical Society of America

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A technique for modifying vocal tract area functions is developed by using sum and difference combinations of acoustic sensitivity functions to perturb an initial vocal tract configuration. First, sensitivity functions [e.g., Fant and Pauli, Proc. Speech Comm. Sem. 74, 1975] are calculated for a given area function, at its specific formant frequencies. The sensitivity functions are then multiplied by scaling coefficients that are determined from the difference between a desired set of formant frequencies and those supported by the current area function. The scaled sensitivity functions are then summed together to generate a perturbation of the area function. This produces a new area function whose associated formant frequencies are closer to the desired values than the previous one. This process is repeated iteratively until the coefficients are equal to zero or are below a threshold value.

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“…For vowels, acoustic distance measures between natural and synthesized formant frequencies are, therefore, often minimized. 18,19 Cepstral distance measures are also useful and very flexible 11,20,21 and will be discussed below in Sec. II E.…”

Section: Introduction and Review Of Previous Workmentioning

confidence: 99%

“…17 The use of articulatory models to constrain the VT area function, regularization and continuity terms in the cost function, and initialization using articulatory codebooks helps to resolve the non-uniqueness and local optima issues in analysis-by-synthesis. 9,[11][12][13][14]18 (3) Incomplete knowledge about the shape and dynamics of the VT for a given speaker. (4) Insufficient data to learn from or to evaluate inversion results.…”

Section: Introduction and Review Of Previous Workmentioning

confidence: 99%

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

Panchapagesan

Alwan

2011

The Journal of the Acoustical Society of America

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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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Determination of vocal tract shape for vowels

Cited by 18 publications

References 9 publications

Extraction of vocal-tract system characteristics from speech signals

Extraction of vocal-tract system characteristics from speech signals

Technique for “tuning” vocal tract area functions based on acoustic sensitivity functions

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

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