Coup de glotte | EPFL Graph Search

Le coup de glotte ou consonne occlusive glottale est une consonne dont la description en phonétique articulatoire est l'occlusive glottale sourde, notée en alphabet phonétique international, dans la transcription traditionnelle des langues sémitiques et dans l'alphabet hawaïen (signe nommé ʻokina) et la plupart des autres langues polynésiennes. C'est parfois une apostrophe qui est employée à la place de ces deux derniers signes. La consonne est la première dans l'ordre alphabétique dit « levantin » (dans lequel on commence par ou a, b, g ou c, d, etc.) de nombreuses écritures sémitiques (alphabet arabe, alphabet hébreu, alphabet phénicien, etc.). Dans les alphabets occidentaux, cette première place est occupée par la lettre qui note /a/. Le premier alphabet qui utilise l'ordre levantin, ancêtre pour le principe mais non pour le tracé des lettres de tous les autres alphabets utilisant un tel ordre (en gros ceux descendant de l'alphabet phénicien : alphabet grec, d'où alphabet étrusque, alphabet latin, alphabet cyrillique, alphabet gotique et alphabet copte ; alphabet araméen d'où alphabet hébreu, alphabet syriaque, alphabet arabe, etc.), est l'alphabet ougaritique, qui est une écriture cunéiforme. Dans cet alphabet (en fait un abjad, seules les consonnes étant notées), dont on possède plusieurs tablettes abécédaires (qui donnent les graphèmes dans un ordre établi. Une tablette de 1955 trouvée à Ougarit donne même, bien qu'incomplètement, l'équivalent en akkadien, modèle de l'ougaritique), la première lettre est un coup de glotte (maintenant noté ). L'alphabet ougaritique n'étant cependant pas capable de représenter la consonne seule, la première lettre est et non (d'où les signes additionnels ajoutés en fin d'alphabet pour et ). D'après John Healey (cf. bibliographie), , et pouvaient même servir à noter parfois , et , plus rarement de pures voyelles.

Multi-parametric source-filter separation of speech and prosodic voice restoration

Olaf Schleusing

In this thesis, methods and models are developed and presented aiming at the estimation, restoration and transformation of the characteristics of human speech. During a first period of the thesis, a concept was developed that allows restoring prosodic voice features and reconstruct more natural sounding speech from pathological voices using a multi-resolution approach. Inspired from observations with respect to this approach, the necessity of a novel method for the separation of speech into voice source and articulation components emerged in order to improve the perceptive quality of the restored speech signal. This work subsequently represents the main part of this work and therefore is presented first in this thesis. The proposed method is evaluated on synthetic, physically modelled, healthy and pathological speech. A robust, separate representation of source and filter characteristics has applications in areas that go far beyond the reconstruction of alaryngeal speech. It is potentially useful for efficient speech coding, voice biometrics, emotional speech synthesis, remote and/or non-invasive voice disorder diagnosis, etc. A key aspect of the voice restoration method is the reliable separation of the speech signal into voice source and articulation for it is mostly the voice source that requires replacement or enhancement in alaryngeal speech. Observations during the evaluation of above method highlighted that this separation is insufficient with currently known methods. Therefore, the main part of this thesis is concerned with the modelling of voice and vocal tract and the estimation of the respective model parameters. Most methods for joint source filter estimation known today represent a compromise between model complexity, estimation feasibility and estimation efficiency. Typically, single-parametric models are used to represent the source for the sake of tractable optimization or multi-parametric models are estimated using inefficient grid searches over the entire parameter space. The novel method presented in this work proposes advances in the direction of efficiently estimating and fitting multi-parametric source and filter models to healthy and pathological speech signals, resulting in a more reliable estimation of voice source and especially vocal tract coefficients. In particular, the proposed method is exhibits a largely reduced bias in the estimated formant frequencies and bandwidths over a large variety of experimental conditions such as environmental noise, glottal jitter, fundamental frequency, voice types and glottal noise. The methods appears to be especially robust to environmental noise and improves the separation of deterministic voice source components from the articulation. Alaryngeal speakers often have great difficulty at producing intelligible, not to mention prosodic, speech. Despite great efforts and advances in surgical and rehabilitative techniques, currently known methods, devices and modes of speech rehabilitation leave pathological speakers with a lack in the ability to control key aspects of their voice. The proposed multiresolution approach presented at the end of this thesis provides alaryngeal speakers an intuitive manner to increase prosodic features in their speech by reconstructing a more intelligible, more natural and more prosodic voice. The proposed method is entirely non-invasive. Key prosodic cues are reconstructed and enhanced at different temporal scales by inducing additional volatility estimated from other, still intact, speech features. The restored voice source is thus controllable in an intuitive way by the alaryngeal speaker. Despite the above mentioned advantages there is also a weak point of the proposed joint source-filter estimation method to be mentioned. The proposed method exhibits a susceptibility to modelling errors of the glottal source. On the other hand, the proposed estimation framework appears to be well suited for future research on exactly this topic. A logical continuation of this work is the leverage the efficiency and reliability of the proposed method for the development of new, more accurate glottal source models.

EPFL2012

Multi-parametric source-filter separation of speech and prosodic voice restoration

Olaf Schleusing

EPFL2012