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Estimation of the Vocal Tract Length of Vowel Sounds based on the Frequency of the Significant Spectral Valley

Ananthapadmanabha, TV and Ramakrishnan, AG (2018) Estimation of the Vocal Tract Length of Vowel Sounds based on the Frequency of the Significant Spectral Valley. In: Proceedings of the Annual Conference of the International Speech Communication Association, 2-6th Sept., 2018, Hyderabad International Convention Centre (HICC)Hyderabad; India, pp. 2102-2106.

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Official URL: https://dx.doi.org/10.21437/Interspeech.2018-1105


Estimating the vocal tract length (VTL), given the acoustic signal of a vowel sound, is an important problem, which is useful in speaker normalization for vowel recognition, in the inversion problem and in acoustic-phonetic studies. The common approach of using the formant data to estimate VTL works for a neutral vowel approximating a uniform tube. However, for natural vowels, formant data shift considerably away from the resonant frequencies of a uniform tube. The proposed method is motivated from these observations: (a) the frequency of a spectral valley, F, depends inversely on VTL; (b) there is much smaller shift in F, across vowels, from the corresponding valley frequency of a uniform tube; (c) F, can be estimated from the spectral envelope itself. VTL has been estimated for the Peterson and Barney (33 male and 28 female speakers) and the TIMIT (326 male and 136 female speakers) databases. When the estimated F is used for normalization, the spread in the formant data due to gender differences is considerably reduced. The normalization procedure is vowel and speaker intrinsic. Additionally, we report applications such as front/back classification, gender recognition and phonetic feature mapping.

Item Type: Conference Proceedings
Series.: Interspeech 2018
Additional Information: 19th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2018), Hyderabad, INDIA, AUG 02-SEP 06, 2018
Keywords: vocal tract length; speaker normalization; spectral valley; front/back classification; gender recognition
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 10 Aug 2020 10:47
Last Modified: 10 Aug 2020 10:47
URI: http://eprints.iisc.ac.in/id/eprint/62923

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