Applied Harmonic Analysis and Data Science (hybrid meeting)

Data science has become a field of major importance for science and technology nowadays and poses a large variety of challenging mathematical questions. The area of applied harmonic analysis has a significant impact on such problems by providing methodologies both for theoretical questions and for a wide range of applications in signal and image processing and machine learning. Building on the success of three previous workshops on applied harmonic analysis in 2012, 2015 and 2018, this workshop focused on several exciting novel directions such as mathematical theory of deep learning, but also reported progress on long-standing open problems in the field

Models and analysis of vocal emissions for biomedical applications: 5th International Workshop: December 13-15, 2007, Firenze, Italy

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies. The Workshop has the sponsorship of: Ente Cassa Risparmio di Firenze, COST Action 2103, Biomedical Signal Processing and Control Journal (Elsevier Eds.), IEEE Biomedical Engineering Soc. Special Issues of International Journals have been, and will be, published, collecting selected papers from the conference

Theoretical estimates of equilibrium sulfur isotope effects in aqueous sulfur systems : highlighting the role of isomers in the sulfite and sulfoxylate systems

© The Author(s), 2016. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Geochimica et Cosmochimica Acta 195 (2016): 171-200, doi:10.1016/j.gca.2016.09.021.We present theoretical calculations for all three isotope ratios of sulfur (33S/32S, 34S/32S, 36S/32S) at the B3LYP/6-31+G(d,p) level of theory for aqueous sulfur compounds modeled in 30–40H2O clusters spanning the range of sulfur oxidation state (Sn, n = −2 to +6) for estimating equilibrium fractionation factors in aqueous systems. Computed 34β values based on major isotope (34S/32S) reduced partition function ratios (RPFRs) scale to a first order with sulfur oxidation state and coordination, where 34β generally increase with higher oxidation state and increasing coordination of the sulfur atom. Exponents defining mass dependent relationships based on β values (x/34κ = ln(xβ)/ln(34β), x = 33 or 36) conform to tight ranges over a wide range of temperature for all aqueous compounds (33/34κ ≈ 0.5148–0.5159, 36/34κ ≈ 1.89–1.90 from T ⩾ 0 °C). The exponents converge near a singular value for all compounds at the high temperature limit (33/34κT→∞ = 0.51587 ± 0.00003 and 36/34κT→∞ = 1.8905 ± 0.0002; 1 s.d. of all computed compounds), and typically follow trends based on oxidation state and coordination similar to those seen in 34β values at lower temperatures. Theoretical equilibrium fractionation factors computed from these β-values are compared to experimental constraints for HSO3−T(aq)/SO2(g, aq), SO2(aq)/SO2(g), H2S(aq)/H2S(g), H2S(aq)/HS−(aq), SO42−(aq)/H2ST(aq), S2O32−(aq) (intramolecular), and S2O32−(aq)/H2ST(aq), and generally agree within a reasonable estimation of uncertainties. We make predictions of fractionation factors where other constraints are unavailable. Isotope partitioning of the isomers of protonated compounds in the sulfite and sulfoxylate systems depend strongly on whether protons are bound to either sulfur or oxygen atoms. The magnitude of the HSO3−T/SO32− major isotope (34S/32S) fractionation factor is predicted to increase with temperature from 0 to 70 °C due to the combined effects of the large magnitude (HS)O3−/SO32− fractionation factor (1000ln34α(HS)bisulfite-sulfite = 19.9‰, 25 °C) relative to the (HO)SO2−/SO32− fractionation factor (1000ln34α(HO)bisulfite–sulfite = −2.2‰, 25 °C), and the increased stability of the (HS)O3− isomer with increasing temperature. We argue that isomerization phenomenon should be considered in models of the sulfur cycle, including models that describe the overall sulfur isotope fractionations associated with microbial metabolism (e.g., microbial sulfate reduction).This work was supported by a NASA Earth and Space Sciences Fellowship (NESSF) granted to D.L. Eldridge (NNX12AL77H), NSF grant 1361945: Sulfur isotope studies of sulfide oxidation (J. Farquhar), and the Investment in Science Fund at WHOI (W. Guo).2018-09-2

HMM-based speech synthesis using an acoustic glottal source model

Parametric speech synthesis has received increased attention in recent years following the development of statistical HMM-based speech synthesis. However, the speech produced using this method still does not sound as natural as human speech and there is limited parametric flexibility to replicate voice quality aspects, such as breathiness. The hypothesis of this thesis is that speech naturalness and voice quality can be more accurately replicated by a HMM-based speech synthesiser using an acoustic glottal source model, the Liljencrants-Fant (LF) model, to represent the source component of speech instead of the traditional impulse train. Two different analysis-synthesis methods were developed during this thesis, in order to integrate the LF-model into a baseline HMM-based speech synthesiser, which is based on the popular HTS system and uses the STRAIGHT vocoder. The first method, which is called Glottal Post-Filtering (GPF), consists of passing a chosen LF-model signal through a glottal post-filter to obtain the source signal and then generating speech, by passing this source signal through the spectral envelope filter. The system which uses the GPF method (HTS-GPF system) is similar to the baseline system, but it uses a different source signal instead of the impulse train used by STRAIGHT. The second method, called Glottal Spectral Separation (GSS), generates speech by passing the LF-model signal through the vocal tract filter. The major advantage of the synthesiser which incorporates the GSS method, named HTS-LF, is that the acoustic properties of the LF-model parameters are automatically learnt by the HMMs. In this thesis, an initial perceptual experiment was conducted to compare the LFmodel to the impulse train. The results showed that the LF-model was significantly better, both in terms of speech naturalness and replication of two basic voice qualities (breathy and tense). In a second perceptual evaluation, the HTS-LF system was better than the baseline system, although the difference between the two had been expected to be more significant. A third experiment was conducted to evaluate the HTS-GPF system and an improved HTS-LF system, in terms of speech naturalness, voice similarity and intelligibility. The results showed that the HTS-GPF system performed similarly to the baseline. However, the HTS-LF system was significantly outperformed by the baseline. Finally, acoustic measurements were performed on the synthetic speech to investigate the speech distortion in the HTS-LF system. The results indicated that a problem in replicating the rapid variations of the vocal tract filter parameters at transitions between voiced and unvoiced sounds is the most significant cause of speech distortion. This problem encourages future work to further improve the system

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy

Monitoring voice condition using smartphones

Firenze, ItalySmartphone mediated voice monitoring has the potential to support voice care by facilitating data collection, analysis and biofeedback. To field-test this approach we have developed a smartphone app that allows recording of voice samples alongside voice self-report data. Our longterm aim is convenient and accessible voice monitoring to prevent voice problems and disorders. Our current study focussed on the automatic detection of voice changes in healthy voices that result from common transient illnesses like colds. We have recorded a database of approximately 700 voice samples from 62 speakers and selected a subset of 225 voice samples from 8 speakers who had submitted at least 10 recordings and reported at least one instance of a moderate cold. We extracted 12 acoustic parameters and applied multivariate statistical process control procedures (Hotelling's T2) to detect whether instances of cold caused violations of distributional control limits. Results showed significant association between control limit violations and reporting of a cold. While there is scope for further improvement of sensitivity and specificity of the procedure, it could already support early detection of voice problems, especially if mediated by voice experts.http://www.fupress.comcaslpub4892pu

Models and analysis of vocal emissions for biomedical applications

This book of Proceedings collects the papers presented at the 3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003, held 10-12 December 2003, Firenze, Italy. The workshop is organised every two years, and aims to stimulate contacts between specialists active in research and industrial developments, in the area of voice analysis for biomedical applications. The scope of the Workshop includes all aspects of voice modelling and analysis, ranging from fundamental research to all kinds of biomedical applications and related established and advanced technologies