Estimation of the glottal flow from speech pressure signals: Evaluation of three variants of iterative adaptive inverse filtering using computational physical modelling of voice production

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Mokhtari, Parham
dc.contributor.author Story, Brad
dc.contributor.author Alku, Paavo
dc.contributor.author Ando, Hiroshi
dc.date.accessioned 2018-10-02T11:31:49Z
dc.date.available 2018-10-02T11:31:49Z
dc.date.issued 2018
dc.identifier.citation Mokhtari , P , Story , B , Alku , P & Ando , H 2018 , ' Estimation of the glottal flow from speech pressure signals: Evaluation of three variants of iterative adaptive inverse filtering using computational physical modelling of voice production ' Speech Communication , vol 104 , pp. 24-38 . DOI: 10.1016/j.specom.2018.09.005 en
dc.identifier.issn 0167-6393
dc.identifier.issn 1872-7182
dc.identifier.other PURE UUID: da9575fc-10f6-427a-a9e3-28110dbc1ecb
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/estimation-of-the-glottal-flow-from-speech-pressure-signals-evaluation-of-three-variants-of-iterative-adaptive-inverse-filtering-using-computational-physical-modelling-of-voice-production(da9575fc-10f6-427a-a9e3-28110dbc1ecb).html
dc.identifier.other PURE LINK: http://www.sciencedirect.com/science/article/pii/S0167639318301316
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/28018250/ELEC_Mokhtari_et_al_Estimation_of_the_glottal_Speech_Comm.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/34135
dc.description.abstract The aim of this study is to comparatively review and evaluate three variants of the glottal inverse filtering algorithm based on iterative adaptive inverse filtering (IAIF): the Standard algorithm, and two recently proposed variants that use iterative optimal preemphasis (IOP) and a glottal flow model (GFM), respectively. To enable an objective evaluation, a computational physical model of voice production is used to generate time-domain signals pertaining to both the input glottal flow and the output speech pressure, for a wide range of vowels, fundamental frequencies, and voice qualities (involving co-variation of phonation type and loudness). Furthermore, for a fair comparison, the three key parameters of IAIF are selected by an exhaustive search to minimize the root-mean-square error between the estimated and reference glottal flow derivative in each analyzed frame and performance is assessed with two time-domain and two frequency-domain error measures. A conventional evaluation is also carried out with fixed parameter values determined by cross-validation. Results indicate that IOP tends to yield the lowest errors for nonback vowels (reducing errors by 31% on average compared with Standard), especially for not too high fundamental frequencies and not too pressed voice qualities; GFM becomes competitive for normal phonations when fixed parameter values are used; and in other cases, Standard IAIF is still recommended. In addition, the results suggest that not only the overall spectral tilt (as controlled by IOP and GFM) but also the balance between the levels of different spectral regions, can be important for accurate estimation of the glottal flow. en
dc.format.extent 15
dc.format.extent 24-38
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries Speech Communication en
dc.relation.ispartofseries Volume 104 en
dc.rights openAccess en
dc.subject.other 113 Computer and information sciences en
dc.title Estimation of the glottal flow from speech pressure signals: Evaluation of three variants of iterative adaptive inverse filtering using computational physical modelling of voice production en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Japan National Institute of Information and Communications Technology
dc.contributor.department University of Arizona
dc.contributor.department Department of Signal Processing and Acoustics
dc.subject.keyword Glottal inverse filtering
dc.subject.keyword IAIF
dc.subject.keyword Voice production
dc.subject.keyword Physical modelling
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201810025218
dc.identifier.doi 10.1016/j.specom.2018.09.005
dc.type.version publishedVersion


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