Literature DB >> 12243162

A quasiarticulatory approach to controlling acoustic source parameters in a Klatt-type formant synthesizer using HLsyn.

Helen M Hanson1, Kenneth N Stevens.   

Abstract

The HLsyn speech synthesizer uses models of the vocal tract to map higher-level quasiarticulatory parameters to the acoustic parameters of a Klatt-type formant synthesizer. The benefits of this system are several. In addition to requiring a relatively small number of parameters, the HLsyn model includes constraints on source-filter relations that occur naturally during speech production. Such constraints help to prevent combinations of sources and filter that are impossible to achieve with the human vocal tract. Thus, HLsyn could lead to reductions in the complexity of formant synthesis and result in better quality synthesis. HLsyn can also be a useful tool for speech-science education and speech research. This paper focuses on the generation of acoustic sources in HLsyn. Described in detail are the equations and methods used to estimate Klatt-type source parameters from HLsyn parameters. Several examples illustrating the generation of source parameters for obstruents (voiced and voiceless) and sonorants are provided. Future papers will describe the filtering components of HLsyn.

Entities:  

Mesh:

Year:  2002        PMID: 12243162     DOI: 10.1121/1.1498851

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


  10 in total

1.  Perception of articulatory dynamics from acoustic signatures.

Authors:  Khalil Iskarous; Hosung Nam; D H Whalen
Journal:  J Acoust Soc Am       Date:  2010-06       Impact factor: 1.840

2.  Quantifying the adequacy of neural representations for a cross-language phonetic discrimination task: prediction of individual differences.

Authors:  Rajeev D S Raizada; Feng-Ming Tsao; Huei-Mei Liu; Patricia K Kuhl
Journal:  Cereb Cortex       Date:  2010-01       Impact factor: 5.357

3.  Effects of obstruent consonants on fundamental frequency at vowel onset in English.

Authors:  Helen M Hanson
Journal:  J Acoust Soc Am       Date:  2009-01       Impact factor: 1.840

4.  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

5.  A procedure for estimating gestural scores from speech acoustics.

Authors:  Hosung Nam; Vikramjit Mitra; Mark Tiede; Mark Hasegawa-Johnson; Carol Espy-Wilson; Elliot Saltzman; Louis Goldstein
Journal:  J Acoust Soc Am       Date:  2012-12       Impact factor: 1.840

6.  Neural bases of categorization of simple speech and nonspeech sounds.

Authors:  Fatima T Husain; Stephen J Fromm; Randall H Pursley; Lara A Hosey; Allen R Braun; Barry Horwitz
Journal:  Hum Brain Mapp       Date:  2006-08       Impact factor: 5.038

7.  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

8.  Dynamical account of how /b, d, g/ differ from /p, t, k/ in Spanish: Evidence from labials.

Authors:  Benjamin Parrell
Journal:  Lab Phonol       Date:  2011-10-01

9.  Consonantal F0 perturbation in American English involves multiple mechanisms.

Authors:  Yi Xu; Anqi Xu
Journal:  J Acoust Soc Am       Date:  2021-04       Impact factor: 1.840

10.  The use of acoustic cues for phonetic identification: effects of spectral degradation and electric hearing.

Authors:  Matthew B Winn; Monita Chatterjee; William J Idsardi
Journal:  J Acoust Soc Am       Date:  2012-02       Impact factor: 2.482

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.