Generative Modelling for Unsupervised Score Calibration

Score calibration enables automatic speaker recognizers to make cost-effective accept / reject decisions. Traditional calibration requires supervised data, which is an expensive resource. We propose a 2-component GMM for unsupervised calibration and demonstrate good performance relative to a supervised baseline on NIST SRE'10 and SRE'12. A Bayesian analysis demonstrates that the uncertainty associated with the unsupervised calibration parameter estimates is surprisingly small.Comment: Accepted for ICASSP 201

ROBUST SPEAKER RECOGNITION BASED ON LATENT VARIABLE MODELS

Automatic speaker recognition in uncontrolled environments is a very challenging task due to channel distortions, additive noise and reverberation. To address these issues, this thesis studies probabilistic latent variable models of short-term spectral information that leverage large amounts of data to achieve robustness in challenging conditions. Current speaker recognition systems represent an entire speech utterance as a single point in a high-dimensional space. This representation is known as "supervector". This thesis starts by analyzing the properties of this representation. A novel visualization procedure of supervectors is presented by which qualitative insight about the information being captured is obtained. We then propose the use of an overcomplete dictionary to explicitly decompose a supervector into a speaker-specific component and an undesired variability component. An algorithm to learn the dictionary from a large collection of data is discussed and analyzed. A subset of the entries of the dictionary is learned to represent speaker-specific information and another subset to represent distortions. After encoding the supervector as a linear combination of the dictionary entries, the undesired variability is removed by discarding the contribution of the distortion components. This paradigm is closely related to the previously proposed paradigm of Joint Factor Analysis modeling of supervectors. We establish a connection between the two approaches and show how our proposed method provides improvements in terms of computation and recognition accuracy. An alternative way to handle undesired variability in supervector representations is to first project them into a lower dimensional space and then to model them in the reduced subspace. This low-dimensional projection is known as "i-vector". Unfortunately, i-vectors exhibit non-Gaussian behavior, and direct statistical modeling requires the use of heavy-tailed distributions for optimal performance. These approaches lack closed-form solutions, and therefore are hard to analyze. Moreover, they do not scale well to large datasets. Instead of directly modeling i-vectors, we propose to first apply a non-linear transformation and then use a linear-Gaussian model. We present two alternative transformations and show experimentally that the transformed i-vectors can be optimally modeled by a simple linear-Gaussian model (factor analysis). We evaluate our method on a benchmark dataset with a large amount of channel variability and show that the results compare favorably against the competitors. Also, our approach has closed-form solutions and scales gracefully to large datasets. Finally, a multi-classifier architecture trained on a multicondition fashion is proposed to address the problem of speaker recognition in the presence of additive noise. A large number of experiments are conducted to analyze the proposed architecture and to obtain guidelines for optimal performance in noisy environments. Overall, it is shown that multicondition training of multi-classifier architectures not only produces great robustness in the anticipated conditions, but also generalizes well to unseen conditions

Modelo de gestión de riesgos de TI que contribuye a la operación de procesos core en empresas de telecomunicaciones

La investigación objeto del siguiente documento propone un modelo de gestión de riesgos de TI que contribuye a la operación de los procesos core en las empresas de telecomunicaciones, el sector de telecomunicaciones es un sector que constantemente enfrenta desafíos y los últimos años no fue la excepción, tanto ante nuevas ofertas del mercado y cambios en los hábitos de consumo como amenazas de seguridad, protección de usuarios al acceso a internet y aceleración para una correcta transformación digital. Para el desarrollo del modelo, se ejecutó el proceso de armonización, bajo la metodología de Pardo[1], el proceso tiene como finalidad establecer algunos elementos comunes respecto a diversos modelos propuestos se cumplió con el desarrollo de las fases de la metodología y, finalmente el modelo fue validado mediante juicio de expertos y para medir la confiabilidad de este se empleó Alfa de Cronbach. El objetivo general de la presente investigación fue determinar el impacto de un modelo de gestión de riesgos de ti en la operación de los procesos core en empresas de telecomunicaciones, que luego se reflejaría mediante la implementación parcial del modelo en una empresa del sector. Finalmente se realizó la implementación parcial de nuestro modelo en el servicio de Telefonía Fija de una empresa, donde se identificaron 13 activos críticos que soportan la operación, donde se logró identificar 40 escenarios de riesgos, siendo 09 con criticidad alta; con lo cual se pudo proponer proyectos que ayuden a mitigar los riesgos detectados

Three Cases of Canine Dermatomyositis-Like Disease

Background: Dermatomyositis is an idiopathic, inflammatory/immunemediated disease of the skin, muscles and bloodvessels of hereditary nature and unclear pathogenesis. This familial disease has been described in certain breeds, especially collies and Shetland sheep dogs and is of rare occurrence in mongrel dogs. To describe and discuss three clinical cases of dermatomyositis-like disease and provide a brief review of the literature.Cases: Three young mongrel dogs are included in this report. Case 1: Mandarino, a 4-year-old mongrel dog, having a history of skin lesions for at least a year. Showed an underweight patient, skin ulcers, crusts, alopecia, peri-ocular scarring causing severe lagophthalmia and a corneal ulcer. Muscle atrophy was most notable in the head and legs; the dog haddifficulty and pain walking. Treatment was initialised with cephalexin 30 mg/kg BID, pentoxifylline 25 mg/kg BID, and prednisone 2.2 mg/kg SID. The patient was presented after two weeks for follow up; the anaemia and skin condition had improved, the weight had increased by 2 kg, dysphagia and locomotor abnormalities were not present. Case 2: Milagros,a mongrel female dog approximately two years of age, rescued from a shelter. Physical examination showed facial alopecia, erythema and scarring of the periocular skin, crusting and scaling in alopecic areas, pinnae tip necrosis and crusting, ear alopecia, tail tip necrosis and crusting. Also present were distal limb alopecia, crusting and ulcers in areas of trauma in the hock and carpal surfaces; some nails presented onychorhexis and onychoschizia. The patient has been treated for12 months with a good clinical outcome, with pentoxifylline, azathioprine 2.2 mg/kg EOD alternating with prednisone 1 mg/kg EOD. Case 3: Chuchito, an 11-month-old male mongrel rescued dog had been previously hospitalised due to his skin condition. Physical examination showed depigmented and alopecic areas in the nasal planum, perioral and periocular areas, and inflammation of the palpebral tissues. Necrosis of the distal pinnae, alopecia and scales were evident, along with sloughing of scales and ulcers. Skin lesions were also present in the distal limbs, and alopecia, erythema and some crusting and scales in the carpal, tarsal and digital areas. Onychodystrophy was present in several digits. This study describes the physical examination and the clinical pathological findings, including skin scrapings, fungal cultures, and skin biopsies, in three dogs with dermatomyositis-like disease, as well as the clinical outcomes after slightly different treatment protocols were used. The biopsy results of two dogs showed ischaemic dermatopathy.Discussion: The most common initial signs of the disease are erythema, desquamation and alopecia in the facial area, ears, distal limbs and pinnae in young puppies aged between two and six months of age, followed by pigmentary changes. Muscular lesions are uncommon; when present, they represent the most severe form of this disease. Dysphagia is a common sign and mega-oesophagus may be present. Patients with muscular disease can manifest difficulty walking, with a stiff high gait. The immune mediated pathogenesis of dermatomyositis can relate to triggering factors in some dogs, such as drugs, infections, paraneoplasms, or toxins. Other potential inducing stressors include oestrus, whelping and excessive solar exposure. Dermatomyositis-like or familiar dermatomyositis is diagnosed using clinical findings, histopathologyof skin and muscle, and muscle physiology studies. Electromyography, breed predisposition and genetic background can be helpful in some cases. The clinical findings and response to the treatment of all three cases were compatible with dermatomyositis-like disease in mongrel dogs.Keywords: dermatomyositis, dermatopathy, vascular disease, inflammatory myopathies, mongrel dog

Identification and Characterization of Epithelial Cell-Derived Dense Bodies Produced upon Cytomegalovirus Infection

Dense bodies (DB) are complex, noninfectious particles produced during CMVinfection containing envelope and tegument proteins that may be ideal candidates as vaccines. Although DB were previously described in fibroblasts, no evidence of DB formation has been shown after propagating CMV in epithelial cells. In the present study, both fibroblast MRC-5 and epithelial ARPE-19 cells were used to study DB production during CMV infection. We demonstrate the formation of epithelial cell-derived DB, mostly located as cytoplasmic inclusions in the perinuclear area of the infected cell. DB were gradient-purified, and the nature of the viral particles was confirmed using CMV-specific immunelabeling. Epithelial cell-derived DB had higher density and more homogeneous size (200-300 nm) compared to fibroblast-derived DB (100-600 nm).In agreement with previous results characterizing DB from CMV-infected fibroblasts, the pp65 tegument protein was predominant in the epithelial cell-derived DB. Our results also suggest that epithelial cells had more CMV capsids in the cytoplasm and had spherical bodies compatible with nucleus condensation (pyknosis) in cells undergoing apoptosis that were not detected in MRC-5 infected cells at the tested time post-infection. Our results demonstrate the formation of DB in CMV-infected ARPE-19 epithelial cells that may be suitable candidate to develop a multiprotein vaccine with antigenic properties similar to that of the virions while not including the viral genome.This study was supported by the Spanish Ministry of Science, Innovation and University, Instituto de Salud Carlos III Grant/Award Numbers: PI17CIII-00014 (MPY110/18); PI20CIII-00009 (MPY303/20); DTS18CIII/00006 (MPY127/19). E.G-R is supported by the Sara Borrell Program (CD18CIII/00007), Instituto de Salud Carlos III, Ministerio de Ciencia, Innovación y Universidades. MJR is supported by the PTA Program (PTA2017-14233-I), Ministerio de Ciencia, Innovación y Universidades.S

Effects of types and doses of yeast on gas production and in vitro digestibility of diets containing maize (Zea mays) and lucerne (Medicago sativa) or oat hay

Two yeast products formulated with Saccharomyces cerevisiae were evaluated at the same colonyforming units (CFUs) per gram of substrate. Samples of maize, lucerne and oat hays were mixed (0.5 kg) to a proportion of 80% forage (lucerne or oat) with 20% maize (DM basis) and combined with each yeast to obtain 1.5 x 107 or 3.0 x 107 CFU/g DM. There was also a control without yeast. In vitro gas production was measured at 0, 2, 4, 6, 8, 10, 14, 18, 24, 30, 36, 42, 48, 60, and 72 h incubation. There was no forage/yeast interaction. Both yeast products tended to reduce the maximum volume produced quadratically and lag time linearly, while in vitro dry matter digestibility (IVDMD) increased linearly. Ruminal ammonia N and lactic acid were not affected, whereas methane and carbon dioxide tended to be reduced with the intermediate dose of yeast. When the mixture included oat hay, the total volume of gas increased, the lag time decreased, and there was higher IVDMD than in the lucerne-based mixtures, which were associated with lower methane production. Ammonia and lactic acid remained unchanged. The two yeast products showed the same effects on the dynamics of gas production and in vitro digestibility when dosed at the same number of viable cells or CFUs, and there was no interaction with forage quality

Time-frequency analysis based on minimum-norm spectral estimation to detect induction motor faults

Producción CientíficaIn this work, a new time-frequency tool based on minimum-norm spectral estimation is introduced for multiple fault detection in induction motors. Several diagnostic techniques are available to identify certain faults in induction machines; however, they generally give acceptable results only for machines operating under stationary conditions. Induction motors rarely operate under stationary conditions as they are constantly affected by load oscillations, speed waves, unbalanced voltages, and other external conditions. To overcome this issue, different time-frequency analysis techniques have been proposed for fault detection in induction motors under non-stationary regimes. However, most of them have low-resolution, low-accuracy or both. The proposed method employs the minimum-norm spectral estimation to provide high frequency resolution and accuracy in the time-frequency domain. This technique exploits the advantages of non-stationary conditions, where mechanical and electrical stresses in the machine are higher than in stationary conditions, improving the detectability of fault components. Numerical simulation and experimental results are provided to validate the effectiveness of the method in starting current analysis of induction motors.Consejo Nacional de Ciencia y Tecnología (Proyecto 487058)Universidad de Guanajuato (Proyecto 248495/2019