scholarly journals Modulation Spectra Morphological Parameters: A New Method to Assess Voice Pathologies according to the GRBAS Scale

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Laureano Moro-Velázquez ◽  
Jorge Andrés Gómez-García ◽  
Juan Ignacio Godino-Llorente ◽  
Gustavo Andrade-Miranda
Keyword(s):  
Automatic System ◽  
Feature Space ◽  
Morphological Parameters ◽  
Automatic Evaluation ◽  
Mel Frequency Cepstral Coefficients ◽  
Evaluation Systems ◽  
Voice Pathologies ◽  
Different Levels ◽  
Perceptual Scale

Disordered voices are frequently assessed by speech pathologists using perceptual evaluations. This might lead to problems caused by the subjective nature of the process and due to the influence of external factors which compromise the quality of the assessment. In order to increase the reliability of the evaluations, the design of automatic evaluation systems is desirable. With that in mind, this paper presents an automatic system which assesses the Grade and Roughness level of the speech according to the GRBAS perceptual scale. Two parameterization methods are used: one based on the classic Mel-Frequency Cepstral Coefficients, which has already been used successfully in previous works, and other derived from modulation spectra. For the latter, a new group of parameters has been proposed, named Modulation Spectra Morphological Parameters: MSC, DRB, LMR, MSH, MSW, CIL, PALA, and RALA. In methodology, PCA and LDA are employed to reduce the dimensionality of feature space, and GMM classifiers to evaluate the ability of the proposed features on distinguishing the different levels. Efficiencies of 81.6% and 84.7% are obtained for Grade and Roughness, respectively, using modulation spectra parameters, while MFCCs performed 80.5% and 77.7%. The obtained results suggest the usefulness of the proposed Modulation Spectra Morphological Parameters for automatic evaluation of Grade and Roughness in the speech.

scholarly journals Automatische Evaluation der Humanübersetzung: BLEU vs. METEOR

2020 ◽  
Vol 65 (1) ◽  
pp. 181-205
Author(s):  
Hye-Yeon Chung
Keyword(s):  
Automatic Evaluation ◽  
Human Evaluation ◽  
The Individual

AbstractHuman evaluation (HE) of translation is generally considered to be valid, but it requires a lot of effort. Automatic evaluation (AE) which assesses the quality of machine translations can be done easily, but it still requires validation. This study addresses the questions of whether and how AE can be used for human translations. For this purpose AE formulas and HE criteria were compared to each other in order to examine the validity of AE. In the empirical part of the study, 120 translations were evaluated by professional translators as well as by two representative AE-systems, BLEU/ METEOR, respectively. The correlations between AE and HE were relatively high at 0.849** (BLEU) and 0.862** (METEOR) in the overall analysis, but in the ratings of the individual texts, AE and ME exhibited a substantial difference. The AE-ME correlations were often below 0.3 or even in the negative range. Ultimately, the results indicate that neither METEOR nor BLEU can be used to assess human translation at this stage. But this paper suggests three possibilities to apply AE to compromise the weakness of HE.

scholarly journals Ensemble-Based Out-of-Distribution Detection

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 567
Author(s):  
Donghun Yang ◽  
Kien Mai Mai Ngoc ◽  
Iksoo Shin ◽  
Kyong-Ha Lee ◽  
Myunggwon Hwang
Keyword(s):  
Detection Method ◽  
State Of The Art ◽  
Metric Learning ◽  
Feature Space ◽  
Confidence Score ◽  
Distance Metric Learning ◽  
Current State ◽  
Overall Performance ◽  
Deep Learning Model

To design an efficient deep learning model that can be used in the real-world, it is important to detect out-of-distribution (OOD) data well. Various studies have been conducted to solve the OOD problem. The current state-of-the-art approach uses a confidence score based on the Mahalanobis distance in a feature space. Although it outperformed the previous approaches, the results were sensitive to the quality of the trained model and the dataset complexity. Herein, we propose a novel OOD detection method that can train more efficient feature space for OOD detection. The proposed method uses an ensemble of the features trained using the softmax-based classifier and the network based on distance metric learning (DML). Through the complementary interaction of these two networks, the trained feature space has a more clumped distribution and can fit well on the Gaussian distribution by class. Therefore, OOD data can be efficiently detected by setting a threshold in the trained feature space. To evaluate the proposed method, we applied our method to various combinations of image datasets. The results show that the overall performance of the proposed approach is superior to those of other methods, including the state-of-the-art approach, on any combination of datasets.

scholarly journals The Importance of Environmental Factors in the Planning of Container Terminals: The Case Study of the Port of Augusta

2021 ◽  
Vol 11 (5) ◽  
pp. 2153
Author(s):  
Nadia Giuffrida ◽  
Maja Stojaković ◽  
Elen Twrdy ◽  
Matteo Ignaccolo
Keyword(s):  
Environmental Impact ◽  
Container Terminal ◽  
Decision Support Tool ◽  
Container Terminals ◽  
Mitigation Measures ◽  
Support Tool ◽  
Clean Environment ◽  
Different Levels

Container terminals are the main hubs of the global supply chain but, conversely, they play an important role in energy consumption, environmental pollution and even climate change due to carbon emissions. Assessing the environmental impact of this type of port terminal and choosing appropriate mitigation measures is essential to pursue the goals related to a clean environment and ensuring a good quality of life of the inhabitants of port cities. In this paper the authors present a Terminal Decision Support Tool (TDST) for the development of a container terminal that considers both operation efficiency and environmental impacts. The TDST provides environmental impact mitigation measures based on different levels of evolution of the port’s container traffic. An application of the TDST is conducted on the Port of Augusta (Italy), a port that is planning infrastructural interventions in coming years in order to gain a new role as a reference point for container traffic in the Mediterranean.

scholarly journals Measuring Disability Inclusion Performance in Cities Using Disability Inclusion Evaluation Tool (DIETool)

2020 ◽  
Vol 12 (4) ◽  
pp. 1378 ◽  
Author(s):  
Nataša Rebernik ◽  
Marek Szajczyk ◽  
Alfonso Bahillo ◽  
Barbara Goličnik Marušić
Keyword(s):  
Quality Of Life ◽  
Theory And Practice ◽  
The Political ◽  
Sustainable Cities ◽  
Evaluation Tool ◽  
Sustainable City ◽  
Evaluation Systems ◽  
European Cities ◽  
Technical Developments

Cities are exposed to a growing complexity, diversity and rapid socio-technical developments. One of the greatest challenges is as of how to become fully inclusive to fit the needs of all their citizens, including those with disabilities. Inclusive city, both in theory and practice, still lacks attention. Even in the context of ambitious contemporary concepts, such as smart and sustainable city, the question remains: Do smart and sustainable cities consider inclusiveness of all their inhabitants? Among numerous evaluation systems that measure city’s smartness, sustainability or quality of life, those tackling inclusion are very rare. Specifically, disability inclusion is hardly covered. This may be one of the reasons why cities struggle with applying disability inclusion to practice in a holistic and integrative way. This paper proposes a Disability Inclusion Evaluation Tool (DIETool) and Disability Inclusion Performance Index (DIPI), designed to guide cities through a maze of accessibility and disability inclusion related requirements set within the political, legislative and standardization frameworks. The testing in two European cities shows that the tool is beneficial for providing diagnosis as to how disability friendly a city is, and as such offers an opportunity for designing informed corrective measures towards disability inclusive city design.

scholarly journals Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4418 ◽  
Author(s):  
Aleksandra Sekrecka ◽  
Michal Kedzierski
Keyword(s):  
High Ratio ◽  
Data Sets ◽  
Spectral Quality ◽  
Local Statistics ◽  
Panchromatic Image ◽  
Urbanized Area ◽  
Fusion Methods ◽  
Spatial Quality ◽  
Different Levels

Commonly used image fusion techniques generally produce good results for images obtained from the same sensor, with a standard ratio of spatial resolution (1:4). However, an atypical high ratio of resolution reduces the effectiveness of fusion methods resulting in a decrease in the spectral or spatial quality of the sharpened image. An important issue is the development of a method that allows for maintaining simultaneous high spatial and spectral quality. The authors propose to strengthen the pan-sharpening methods through prior modification of the panchromatic image. Local statistics of the differences between the original panchromatic image and the intensity of the multispectral image are used to detect spatial details. The Euler’s number and the distance of each pixel from the nearest pixel classified as a spatial detail determine the weight of the information collected from each integrated image. The research was carried out for several pan-sharpening methods and for data sets with different levels of spectral matching. The proposed solution allows for a greater improvement in the quality of spectral fusion, while being able to identify the same spatial details for most pan-sharpening methods and is mainly dedicated to Intensity-Hue-Saturation based methods for which the following improvements in spectral quality were achieved: about 30% for the urbanized area and about 15% for the non-urbanized area.

scholarly journals Diet-Regulated Anxiety

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Michelle Murphy ◽  
Julian G. Mercer
Keyword(s):  
Human Population ◽  
Adult Life ◽  
Noncommunicable Disease ◽  
Dietary Manipulation ◽  
Obesogenic Environment ◽  
Preclinical Models ◽  
Societal Challenges ◽  
The Life Course ◽  
Different Levels

A substantial proportion of noncommunicable disease originates in habitual overconsumption of calories, which can lead to weight gain and obesity and attendant comorbidities. At the other end of the spectrum, the consequences of undernutrition in early life and at different stages of adult life can also have major impact on wellbeing and quality of life. To help address some of these issues, greater understanding is required of interactions with food and contemporary diets throughout the life course and at a number of different levels: physiological, metabolic, psychological, and emotional. Here we review the current literature on the effects of dietary manipulation on anxiety-like behaviour. This evidence, assembled from study of preclinical models of diet challenge from gestation to adult life, supports a role for diet in the important connections between psychology, physiology, and behaviour. Analogous processes in the human population in our current obesogenic environment are likely to contribute to individual and societal challenges in this area.

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