Reviewerly/exHarmony huggingface dataset:
Utterance Copy in Formant-Based Speech Synthesizers Using LSTM Neural Networks

Utterance copy, also known as speech imitation, is the task of estimating the parameters of an input, target speech signal in order to artificially reconstruct another signal with the same properties at the output. This can be considered a difficult inverse problem, since the input-output relationship is often non-linear, apart from having several parameters to be estimated and adjusted. This work describes the development of an application that uses a long short-term memory neural network (LSTM) to learn how to estimate the input parameters of thel formant-based Klatt speech synthesizer. Formant-based synthesizers do not reach state-of-art performance for text-to-speech (TTS) applications, but are an important tool for linguists studies due to the high interpretability of its input parameters. The proposed system was compared to the WinSnoori baseline software on both artificially-produced target utterances, generated by the DECtalk TTS system; and natural target ones. Results show that our system outperforms the baseline for synthetic voices on the metrics of PESQ, SNR, RMSE and LSD. For natural voices, the experiments indicate the need for an architecture that does not depend on labeled data, such as reinforcement learning.
On a New Evidential C-Means Algorithm with Instance-Level Constraints

Clustering is an unsupervised task whose performances can be highly improved with background knowledge. As a consequence, several semi-supervised clustering approaches have proposed to integrate prior information in the form of constraints, generally at the instance-level. Amongst them, evidential semi-supervised clustering algorithms, such as CECM or SECM algorithm, rely on the theoretical foundation of belief function which extends the probabilistic theory and allows us to express many types of uncertainty about the assignment of an object to a cluster. In this framework, no evidential clustering algorithm has ever mixed different types of instance-level constraints. We propose here to combine pairwise constraints and labeled data constraints in order to better retrieve information from the background knowledge. The new algorithm, called LPECM, shows good performances on synthetic and real data sets.
An Image Segmentation Method Based on Improved Krill Herd Algorithm and Fuzzy C-Means Clustering Algorithm

Image segmentation is a primary work for machine vi <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> 1This work is funded by National Natural Science Foundation of China, grant number 41301371, 61502155, 61772180, Technological Innovation Project of Hubei Province 2019(2019AAA047), Green Industry Science and Technology Leadership Program of Hubei University of technology (No.CPYF2018005, YXQN2017002) sion and Fuzzy C-Means (FCM) clustering algorithm is one of the commonest methods. However, FCM is sensitive to the initial clustering center and easily falls into the local optimum solution, while the Krill Herd (KH) algorithm has strong global convergence and high stability. As a result, this paper proposes an image segmentation method based on improved Krill Herd algorithm and FCM (IKH-FCM). First of all, the method uses the K-Means algorithm to initialize the initial population of the krill herd, the improved KH algorithm is used to calculate the initial clustering center of FCM, and then FCM clustering is applied to implement image segmentation. Experiments show that the approach has strong global convergence and high stability compared to the original FCM, which is a favorable image segmentation approach for practical work.
Foundation and Cost of Mimic Defense

As pointed out in the previous chapter, the mimic defense is essentially an endogenous security effect formed by the combination of the generalized robust control DHR architecture and the mimic disguise mechanism. It is especially suitable for highly reliable, available, and credible applications that require stability robustness and quality robustness and enjoy better universality in areas such as IT, ICT, CPS, and intelligent control. The related technologies can be used for low-complexity applications such as various software and hardware components, modules, middleware, and IP cores and can also be used for various information processing in control equipment, devices, systems, platforms, facilities, network elements, and even in network environments. Its endogenous security functions should be one of the iconic features of a new generation of information systems. However, the target systems based on the DHR architecture require dedicated or COTS IT products, advanced development tools, and diverse product ecosystems to reduce implementation complexity and cost. The following technological advances or trends have laid an important foundation for the engineering application of mimic defense.
Learning Parameters in Deep Belief Networks Through Ant Lion Optimization Algorithm

Restricted Boltzmann Machine (RBM) has been widely used technologies in the field of deep learning. The RBM model provides good technical support for implementing various parallelisms. Deep Belief Networks are composed of a set of RBMs, and the performance of the DBN model depends in part on the performance of the RBM model. However, the performance of the RBM model affected by the parameters is its main drawback. How to correctly and effectively fine-tune the parameters of the RBM model has not been completely addressed. In this paper, The Ant Lion Optimization (ALO) Algorithm we mentioned is the latest intelligent optimization algorithm, which has good optimization performance and robustness. So, in order to verify our proposed method. First, ALO algorithm and PSO algorithm are used separately to fine-tune the parameters of RBM model, then DBN model stacked by adjusted RBM models are used for image classification. Experimental verifications are conducted on MNIST dataset. The results show that the ALO algorithm has better results.
CREATING TRANSMEDIA NARRATIVES TO ENHANCE DIGITAL INTELLIGENCE IN HIGH SCHOOL STUDENTS

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 9864-9872ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.2413Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
Designing a Conversational User Experience

Building digital assistants without a business case is a recipe for failure. You should always try to answer the key questions before you start like:
Visual Object Tracking by Fusion of Audio Imaging in Template Matching Framework

Audio imaging can play a fundamental role in computer vision, in particular in automated surveillance, boosting the accuracy of current systems based on standard optical cameras.We present here a method for object tracking application that fuses visual image with an audio image in the template-matching framework.Firstly, an improved template matching based tracking is presented that takes care of the chaotic movements in the template-matching algorithm.Then a fusion scheme is presented that makes use of deviations in the correlation scores pattern obtained across the individual frame in each imaging domain.The method is compared with various state of art trackers that perform track estimation using only visible imagery.Results highlight a significant improvement in the object tracking by the assistance of audio imaging using the proposed method under severe challenging vision conditions such as occlusions, object shape deformations, the presence of clutters and camouflage, etc.
AN OPINION MINING MODEL BASED ON USER PREFERENCES

This paper proposes an Opinion Mining model, parameterized according to the reviewer profile.The work aims to highlight and resolve some issues resulting from previous activities in evaluating the goodness of the results obtained by the analysis of the reviews.A user profiling system provides the set of parameters to associate with the aspects and allows, working with the Opinion Mining system, to configure itself according to the user preferences.
USING ROBOTICS IN THE CLASSROOM TO DEVELOP SKILLS NEEDED IN THE 21ST CENTURY WORKPLACE AND TO PROMOTE ENGINEERING HABITS OF MIND

USING ROBOTICS IN THE CLASSROOM TO DEVELOP SKILLS NEEDED IN THE 21ST CENTURY WORKPLACE AND TO PROMOTE ENGINEERING HABITS OF MIND
SUBJECTS “ICT IN EDUCATION” IN TEACHER TRAINING STUDY PROGRAMS AT UNIVERSITIES

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 11621-11629ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.2905Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
Massively Multilingual Sparse Word Representations

In this paper, we introduce Mamus for constructing multilingual sparse word representations. Our algorithm operates by determining a shared set of semantic units which get reutilized across languages, providing it a competitive edge both in terms of speed and evaluation performance. We demonstrate that our proposed algorithm behaves competitively to strong baselines through a series of rigorous experiments performed towards downstream applications spanning over dependency parsing, document classification and natural language inference. Additionally, our experiments relying on the QVEC-CCA evaluation score suggests that the proposed sparse word representations convey an increased interpretability as opposed to alternative approaches. Finally, we are releasing our multilingual sparse word representations for the 27 typologically diverse set of languages that we conducted our various experiments on.
Research of influence of communicative qualities of the pedagogue on the relation of students to educational activity

The article touches upon the topic of pedagogic communication. A review of psychological and pedagogic approaches to the definition of communicative qualities necessary for the pedagogue to organise effective interaction with students, as well as for the organisation of personality-developing educational space. The emotional side of the attitude of students to educational activity, consisting in satisfaction with this activity is considered. Mathematical processing of the data showed the presence of a statistically significant relationship between the degree ofmanifestation of communicative qualities of the pedagogue and the level of satisfaction of students with educational activities in the classes of this pedagogue. It is revealed that the most pronounced relationship of satisfaction with educational activities with indicators of pedagogic cooperation and emotional attractiveness of pedagogues. The author emphasises the need to develop the communicative qualities of future pedagogues in the system of higher pedagogic education. The article will be of interest to specialists, pedagogues of higher education.
Solving the problem of mirroring the signal function with respect to a straight line

The paper deals with the construction of a mirror reflection of the approximating function with respect to a straight line, which can significantly reduce the approximation error for small samples and large noise dispersion.
NEW INFORMATION RETRIEVAL APPROACH BASED ON SEMANTIC INDEXING BY MEANING

An Information Retrieval System (IRS) offers a number of tools and techniques, which enable to locate and visualize the relevant information needed.This information, is expressed by the user in the form of a query natural language.However, the representation of documents and the query in a traditional IRS lead to a lexical-centered relevance estimation which is, in fact, less efficient than a semantic-focused estimation.As a consequence, the documents that are actually relevant are not being recovered if they do not share words with the query, while the documents non relevant, which are words in common with the query, are recovered even though at times they do not have the meaning intended.This paper tackles this problem while suggesting a solution in the level of indexation of an IRS allowing it to improve its performance.To be more precise, we suggest a new approach of semantic indexation allowing to lead to the exact meaning of each term in a document or query undergoing a contextual analysis at the sentence level.In fact, if the system is able to comprehend the need of the user, then consequently it is perfectly capable to respond to it.Add to that, we suggest a simple method allowing to apply any model of IR on our new index table without changing its original bases making it faster.In order to validate this proposed approach, this new created system is evaluated base on numerous collections naming "TIME", "BBC", "The Guardian" and "BigThink".The results based on the experiments indicate the efficacy of our hypothesis compared to traditional IR approaches.
Collaborative learning services in the smart university environment

Smart University (SU) system is significantly based on the deep integration of information technologies in the educationals process, indeed, the emergence of Smart University (SU) concept enable smart learning process by encompassing a range of smart components, which involve the implementation of an adaptive educational model using informational smart technologies. Through a process of interaction between academics and the organizational structure, it promotes modern methods of collaboration to increase the success and effectiveness of education. The service-oriented paradigm is crucial in ensuring a collaborative learning environment, which boosted by intelligent layers, additional treatment and data-powered. The paper concludes with "smart collaborative learning", as a relevant concept that adopts smart interactions to promotes modern methods of collaboration between teams of smart learners.
The affordances of technology for teaching indigenous knowledge

This book is the result of a longitudinal research project (2016–2018) funded by the National Research Foundation and the Fuchs Foundation, and it disseminates original research. The project researched the affordances of indigenous knowledge in the school science, technology and mathematics curricula. Short learning programmes (SLPs) were offered to STEM teachers, during which they engaged in creative and inquiry-based teaching and learning strategies. Research shows that strategies such as problem-based and cooperative learning have the potential to enhance self-directed learning. This design-based research was conducted in several provinces in South Africa (North-West Province, the Northern Cape, Limpopo Province, and in Gauteng). Based on the data obtained after each intervention, design principles were formulated for redesigning of SLPs. The qualitative research focussed on teachers’ lived experiences of the epistemological border-crossing between natural science and indigenous knowledge, their views on the nature of science and indigenous knowledge, and the reformed teaching and learning that took place after the intervention, in teachers’ classrooms.
Justin Richer on OAuth

In Episode 376 of “Software Engineering Radio,” Justin Richer, lead author of OAuth2 in Action and editor of OAuth extensions RFC 7591, 7592, and 7662, discusses the key technical features of the OAuth 2.0 protocol for authorization. Gavin Henry spoke with Richer about browser-based OAuth2, types of tokens, OpenID Connect, PKCE, JavaScript Object Notation Web Token pros and cons, where to store them, client secrets, single-page apps, mobile apps, current best practices, OAuth.XYZ, HEART, MITREid, token validation, dynamic client registration, the decision factors of the various types of authorization grants to use, and what is next for OAuth. To hear the full interview, visit http://www.se-radio.net or access our archives via RSS at http:// feeds.feedburner.com/se-radio.
View-Invariant and Similarity Learning for Robust Person Re-Identification

Person re-identification aims to identify pedestrians across non-overlapping camera views. Deep learning methods have been successfully applied to solving the problem and have achieved impressive results. However, these methods rely either on feature extraction or metric learning alone ignoring the joint benefit and mutual complementary effects of the person view-specific representation. In this paper, we propose a multi-view deep network architecture coupled with n-pair loss (JNPL) to eliminate the complex view discrepancy and learn nonlinear mapping functions that are view-invariant. We show that the problem of the large variation in viewpoints of a pedestrian can be well solved using a multi-view network. We simultaneously exploit the complementary representation shared between views and propose an adaptive similarity loss function to better learn a similarity metric. In detail, we first extract view-invariant feature representation from n-pair of images using multi-stream CNN and then aggregate these features for predictions. Given n-positive pairs and a negative example, the network aggregate the feature map of the n-positive pairs and predicts the identity of the person and at the same time learns features that discriminate positive pairs against the negative sample. Extensive evaluations on three large scale datasets demonstrate the substantial advantages of our method over existing state-of-art methods.
PERSONALIZATION IN SERIOUS GAMES FOR ASSESSMENT

1 Arts, Sciences & Technology University in Lebanon (LEBANON)2 University of Sousse (TUNISIA)3 Alexandria University (EGYPT)
Manipulating photonic signals by a multipurpose quantum junction

We address a prototype integrated quantum circuit model system: a multifunctional quantum junction comprising three-level atomic nodes that couple two waveguides. We consider nodes with the $\mathrm{\ensuremath{\Lambda}}$ scheme of the allowed optical transitions, one of which is driven by an external classical electromagnetic field. We demonstrate that the latter field can be used to control the mode of the device operation: studying the dynamics of optical pulses, we show that the proposed integrated junction can operate as a controlled router or a switch, a 1/4 splitter, a delay line, or a storage node. The system offers also a possibility of intrinsic parallelism of quantum operations and can provide useful guidelines for making possible future quantum circuitry building blocks more scalable and integrated.
ORGANIZATION AND MANAGEMENT OF EDUCATION, EDUCATIONAL POLICY AND EVALUATION OF THE INSTITUTION OF GREEK SECONDARY INTERCULTURAL EDUCATION

ORGANIZATION AND MANAGEMENT OF EDUCATION, EDUCATIONAL POLICY AND EVALUATION OF THE INSTITUTION OF GREEK SECONDARY INTERCULTURAL EDUCATION
APPLICATION OF ARDUINO FOR THE TEACHING OF MATHEMATICS IN PRIMARY EDUCATION

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 6316-6321ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.1524Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
STRUKTUR KOMUNITAS ANNELIDA SEBAGAI BIOINDIKATOR PENCEMARAN SUNGAI ANCAR KOTA MATARAM

Ancar River is a river that is used by many residents for various activities, such as agricultural activities, fisheries, and planting water spinach. In addition to these activities, the Ancar River is also used as a place for domestic waste disposal and disposal of the tofu waste industry so that it can have a negative impact on water resources, including causing a decrease in water quality. The Annelida response to environmental changes can be used to see the effect of various activities, such as the impact of industrial activities, agriculture, and land use. This study aims to assess the community structure of Annelida as bioindicators of the waters against the content of polluted material found in the Ancar River. This research is descriptive explorative, using quantitative and qualitative approaches. This study uses the "Sampling Purposive" method, which is the determination of the observation station based on the use of land around the Ancar River environment. Each sampling station is carried out in 3 points, namely left, center and right of the river. Annelida obtained in the Ancar River consist of two classes namely Oligochaeta and Hirudinea. Oligochaeta class consists of Tubifex sp., Lumbricus terrestris, Hirudinea class consisting of Hirudo medicinalis. The community structure of Annelida can be used as a indicator of river pollution. From the results of the study it was found that the Ancar River had experienced pollution caused by organic matter both from household waste and tofu industrial waste. Based on the BOD value it is known that station 1 is categorized as uncontaminated location, stations 2 and 4 are lightly polluted, and stations 3, 5 and 6 are moderately polluted.
Qualitative and quantitative Analysis of consumers perception regarding anthropomorphic AI designs

Abstract Business intelligence and analytics are nowadays being integrated into diverse industries, from healthcare to customer relationship management and behavioral profiling, due to the competitive advantages that they offer. Nevertheless, most companies try to integrate as many forms of business intelligence systems as possible into different internal processes. This overall digitization applied to more and more business departments is being analyzed with both curiosity and reluctance. The decision regarding the implementation of innovative forms of automation is taken in an attempt to discover and solve business challenges. However, there are several issues involved, which need to be addressed. One of the risks that are being discussed in the research environment refers to the level of acceptance of artificial intelligence systems. The tolerance and overall readiness of the consumers towards innovation and technology is one of the critical factors which need to be determined before implementing disruptive business intelligence systems. Moreover, in an effort to make devices friendlier to consumers, some developers chose to assign anthropomorphic appearances and even create individual identities for each artificial intelligence system. In this context, it is important for most companies investing in intelligent automation systems to determine to which extend the use of anthropomorphic designs impacts the customer’s perception. The objective of this research paper is to analyze the unconscious reaction of consumers towards two opposite designs of artificial intelligence systems: a robotic-like form and a human-like design. Based on this difference, a photo collage was created figuring two pictures: one with a metallic robot having a conversation with a human being and one with a robot with a strong anthropomorphic figure found in the same situation. For the analysis, an eye tracking device was used, in order to measure the point of gaze, the unconscious motion of the eyes, along with the time spent on each fixation and the order in which different elements were fixated upon by the respondents. As the eye-tracking device can generate data in various forms, this research includes both qualitative and quantitative analyses of the results, which confirm the same hypothesis, regarding the consumer’s preference towards artificial intelligence systems with robotic designs.