Voicing quantification is more relevant than period perturbation in substitution voices: an advanced acoustical study

Quality of substitution voicing—i.e., phonation with a voice that is not generated by the vibration of two vocal folds—cannot be adequately evaluated with routinely used software for acoustic voice analysis that is aimed at ‘common’ dysphonias and nearly periodic voice signals. The AMPEX analysis program (Van Immerseel and Martens) has been shown previously to be able to detect periodicity in irregular signals with background noise, and to be suited for running speech. The validity of this analysis program is first tested using realistic synthesized voice signals with known levels of cycle-to-cycle perturbations and additive noise. Second, exhaustive acoustic analysis is performed of the voices of 116 patients surgically treated for advanced laryngeal cancer and recorded in seven European academic centers. All of them read out a short phonetically balanced passage. Patients were divided into six groups according to the oscillating structures they used to phonate. Results show that features related to quantification of voicing enable a distinction between the different groups, while the features reporting F0-instability fail to do so. Acoustic evaluation of voice quality in substitution voices thus best relies upon voicing quantification

Structural relationship between link proteins and proteoglycan monomers

AbstractStructural homologies between link proteins and proteoglycan monomers are demonstrated. A possible redundancy in the proteoglycan monomers structure is discussed and the link proteins domains homologous to other proteins are specified

The Supervision of Speech Production

Introduction Since the emergence of phonology as a component within the generative paradigm of linguistics there has been discussion concerning how it relates to phonetics. At least two views of the relationship are possible: € Phonology describes the same data as phonetics, but whereas phonetics models physical detail phonology models abstract relationships holding between units within the data. These units are defined within the general framework of linguistic theory. € Phonology stands logically prior to phonetics, and the output of its processes comprises the input to phonetics. Phonetics itself is a processing component producing an output. The model can be regarded as static, involving no temporal relationship (the usual view in linguistics), or it can be regarded as dynamic. The dynamic view is often taken when the theory is used to support work in an allied area, for example in speech technology, where temporal as well as logical relationships between processes are important. It is usually understood that phonetic processes are of little concern to linguistics, and that by the output of phonology all linguistic processing is complete. Phonetic realisation of phonological 'requirements' is thought of as a passive process involving no cognitive processing, and introducing nothing new of linguistic consequence or interest. For example, phonologists working on language acquisition are interested in the phonetic constraints on what can be acquired by a child, but are not concerned with the detail of phonetic processes. The most extreme form of this position would be that speech processing of a cognitive nature falls within the province of phonology, but that all physical processing falls within the province of phonetics. Since, by definition, language is a cognitive system it can have nothing formal to do with phonetics, except in its trivial realisational rôle. There has recently been a trend toward a more phonetic approach to phonology, 1,2 and a greater awareness among phoneticians of the abstractions ofphonology3 and why they are necessary. This paper will consider how ARTICULATORY PHONOLOGY might handle some phonetic data, and attempt to deal with some problems that the data points up in the theory

Suppression of Raf-1 kinase activity and MAP kinase signalling by RKIP

Raf-1 phosphorylates and activates MEK-1, a kinase that activates the extracellular signal regulated kinases (ERK). This kinase cascade controls the proliferation and differentiation of different cell types. Here we describe a Raf-1-interacting protein, isolated using a yeast two-hybrid screen. This protein inhibits the phosphorylation and activation of MEK by Raf-1 and is designated RKIP (Raf kinase inhibitor protein). In vitro, RKIP binds to Raf-1, MEK and ERK, but not to Ras. RKIP co-immunoprecipitates with Raf-1 and MEK from cell lysates and colocalizes with Raf-1 when examined by confocal microscopy. RKIP is not a substrate for Raf-1 or MEK, but competitively disrupts the interaction between these kinases. RKIP overexpression interferes with the activation of MEK and ERK, induction of AP-1-dependent reporter genes and transformation elicited by an oncogenically activated Raf-1 kinase. Downregulation of endogenous RKIP by expression of antisense RNA or antibody microinjection induces the activation of MEK-, ERK- and AP-1-dependent transcription. RKIP represents a new class of protein-kinase-inhibitor protein that regulates the activity of the Raf/MEK/ERK modul

Ligand Binding Study of Human PEBP1/RKIP: Interaction with Nucleotides and Raf-1 Peptides Evidenced by NMR and Mass Spectrometry

Background Human Phosphatidylethanolamine binding protein 1 (hPEBP1) also known as Raf kinase inhibitory protein (RKIP), affects various cellular processes, and is implicated in metastasis formation and Alzheimer's disease. Human PEBP1 has also been shown to inhibit the Raf/MEK/ERK pathway. Numerous reports concern various mammalian PEBP1 binding ligands. However, since PEBP1 proteins from many different species were investigated, drawing general conclusions regarding human PEBP1 binding properties is rather difficult. Moreover, the binding site of Raf-1 on hPEBP1 is still unknown. Methods/Findings In the present study, we investigated human PEBP1 by NMR to determine the binding site of four different ligands: GTP, FMN, and one Raf-1 peptide in tri-phosphorylated and non-phosphorylated forms. The study was carried out by NMR in near physiological conditions, allowing for the identification of the binding site and the determination of the affinity constants KD for different ligands. Native mass spectrometry was used as an alternative method for measuring KD values. Conclusions/Significance Our study demonstrates and/or confirms the binding of hPEBP1 to the four studied ligands. All of them bind to the same region centered on the conserved ligand-binding pocket of hPEBP1. Although the affinities for GTP and FMN decrease as pH, salt concentration and temperature increase from pH 6.5/NaCl 0 mM/20°C to pH 7.5/NaCl 100 mM/30°C, both ligands clearly do bind under conditions similar to what is found in cells regarding pH, salt concentration and temperature. In addition, our work confirms that residues in the vicinity of the pocket rather than those within the pocket seem to be required for interaction with Raf-1.METASU

ICAR: endoscopic skull‐base surgery

n/

Estimation of Formant Frequencies By Means of a Wavelet Transform of the Speech Spectrum

The objective is to present a method that extracts the spectral envelope of a speech signal. The method is based on the wavelet transform, which is a family of multi-resolution analysis methods. The extraction is founded on the observation that spectral envelope and source-related spectral components vary on different frequency scales. The difference between cepstral and wavelet analysis is that the latter is not based on the hypothesis that a speech signal is the outcome of a convolution of the source signal with the vocal tract impulse response. The method of analysis was tested on a corpus of [a],[i],[u] vowels sustained by healthy and dysphonic speakers. Results show that the envelopes extracted via cepstral and wavelet analysis are very similar except in the case of [u], for which the first two formants extracted by means of wavelet analysis are shifted slightly towards higher values and the formant peaks are somewhat closer. Keywords--- Signal Analysis, Cepstrum, Wavelet transfo..