Comparison of parameter sets for temporal decomposition

Dijk-Kappers, Astrid M.L. Van

doi:10.1016/0167-6393(89)90002-2

Cited by 12 publications

(3 citation statements)

References 14 publications

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“…LAR parameters have given better results, i.e. better reconstruction accuracy, in temporal decomposition (Dijk-Kappers, 1989) over the other LPC related spectral parameters. LSF parameters have been known to have the best interpolation properties (Choi, Wong, Cheetham & Goodyear, 1995;Paliwal, 1995), i.e.…”

Section: Simulation Resultsmentioning

confidence: 95%

Spectral stability based event localizing temporal decomposition

Nandasena

Nguyen

Akagi

2001

Computer Speech & Language

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Section: Simulation Resultsmentioning

confidence: 95%

Spectral stability based event localizing temporal decomposition

Nandasena

Nguyen

Akagi

2001

Computer Speech & Language

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“…The collapsing of different phenomena in the real world under the same category is a common capacity that is not limited to humans. Atal, 1983;van Dijk-Kappers and Marcus, 1987;Bimbot, Ahlbom and Chollet, 1987;van Dijk-Kappers, 1988). Various non-human species have been trained to discriminate between the linguistic categories of human speech, but the proper interpretation of these studies remains debatable (see Remez, 1989).…”

Section: The Segment and Its Structurementioning

confidence: 99%

Speech Production and Speech Modelling

Modelling¹,

Hardcastle²,

Marchal³

1990

198

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A Series presenting the results of activities sponsored by the NATO Science Committee, which aims at the dissemination of advanced scientific and technological knowledge, with a view to strengthening links between scientific communities. The Series is published by an international board of publishers in conjunction with the 385) 91, boulevard de I'Hopital 75634 PARIS cedex 13 (France) ABSTRACf. The physiological mechanisms underlying oral communication are of primary interest.Investigations concerning the motor acts of speech are limited to what can be inferred from observation of the peripheral mechanisms of speech production. The neuromuscular events of speech movement patterning are described. In addition, speech movement coordination involves substantial adjustments among the multiple muscles of the various articulatory organs. The cerebellum is an important regulatory center for the control of motor activity. It provides smoothness to the contraction of synergist and antagonist muscles. It uses sensory information to predict, judge and correct the motor act. Damage to a structure with this capability would be expected to have consequences on speech production . The role of the cerebellum in speech control is examined by assessing the effects of cerebellar lesions on speech through a short review of literature.

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“…The set of acoustic parameters chosen by Atal to describe the speech signal y(n) are the log-area parameters. These parameters have a close relationship to the positions of the articulators, vary slowly in time and show a high mutual linear dependence, which makes them eminently suited for temporal decomposition (Van Dijk-Kappers, 1988b). These parameters are derived from the tilter parameters of an LPC analysis; the source parameters do not play a role in temporal decorr~position.…”

Section: Temporal Decompositionmentioning

confidence: 99%

Temporal decomposition of speech

Dijk-Kappers¹,

Marcus²

1989

Speech Communication

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Abstract.In articulatory phonetics speech is described as a sequence of distinct articulatory gestures, each of which produces an acoustic event that should approximate a phonetic target. Due to the overlap of the gestures these phonetic targets are often only partly realized. Atal (1983) has proposed a method for speech coding based on so-called temporal decomposition of speech into a sequence of overlapping target functions and corresponding target vectors. The target vectors may be associated with ideal articulatory positions. The target functions describe the temporal evolution of these targets. This method makes no use of specific articulatoty or phonetic knowledge. We have extended and modified this method to improve the determination of the number and the location of the target functions and to overcome the shortcomings of the original method. With these improvements temporal decomposition has become a strong tool in analysing speech, from which researchers working on speech coding, recognition and synthesis may profit.Zusammenfassung. In der ~. tikulatorischen Phonetik wird die Sprache als eine Folge einzelner Artikulationsgesten beschrieben, die jeweils ein akustisehes Ereignis zur Folge haben, das eine Ann~iherung an ein phonetisches Ziel darstellt. Aufgrund der Oberlappung der Gesten werden diese phonetisehen Ziele oft nut teilweise verwirklicht.Atal (1983) hat eine Methode zur Sprachcodierung vorgeschlagen, die auf der sogenannten Temporalen Dekomposition der Spraehe in eine Folge von iiberlappenden Zielfunktionen und den entsprechenden Zielvektoren beruht, Die Zielvektoten kOnnen idealen Artikulationsstellungen zugeordnet werden. Die Zielfunktionen beschreiben den zeitlichen Entwicklungsverlauf dieser Ziele. Bei dieser Methode werden keine spezifischen Artikulations-oder Phonetik-Kenntnisse angewendet. Wir haben die Methode erweitert und abge~indert, um die Bestimmung yon Anzahl und Position der Zielfunktionen zu verbessern und die Naehteile der urspriinglichen Methode zu umgehen. Durch diese Verbesserungen wurde die Temporale Dekomposition zu einem wertvollen Hilfsmittel in der Sprachanalyse, wovon Forschungen in der Sprachcodierung, -erkennung und -synthese profitieren werden.R~sum~. En phon~tique articulatoire, la parole cst d~crite comme ~tant une s~quence de gestes articulatoires distincts. produisant un ~v~nement acoustique qui devrait se rapprocher d'une cible phon6tique. Du fait du recouvrement des gestes, ces cibles phon6tiques ne sont souvent atteintes qu'en partie.Atal (1983) a propos6 une m6thode permettant le codage de la parole, bas6e sur ce que I'on appelle la d6composition temporelle de la parole en une s6quence de fonctions-cibles de recouvrement et de vecteurs-cibles correspondants. Les vecteurs-cibles peuvent 6tre associ6s ~ des positions articulatoires id6ales. Les fonctions-cibles d~crivent l'6volution temporelle de ees cibles. Cctte m6thode ne requiert pas de connaissances articulatoires ou phon6tiques particuli~res. Nous l'avons 61argie et modifi6e pour mieux d6terminer le nom...

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Comparison of parameter sets for temporal decomposition

Cited by 12 publications

References 14 publications

Spectral stability based event localizing temporal decomposition

Spectral stability based event localizing temporal decomposition

Speech Production and Speech Modelling

Temporal decomposition of speech

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