Search results for: inclusive speech recognition

Authors: Teresa Naves, Katy Pallas, Carme Florit, Cristina Anton, Joan Collado, Diana Millan

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Although gender-fair language is relatively novel in Spain, in Catalonia, the Department of Education, as well as LGBT Associations, have been promoting several innovative programmes aimed at implementing gender-inclusive schools. These Rainbow School communities are ideal for looking at how these programmes affect the use of gender-fair language and the balanced representation of gender. The students' and teachers' perceptions and attitudes have been compared to those analysed in schools that have never implemented such programmes in primary or secondary education. Spanish and Catalan, unlike English, are gendered languages in which masculine forms have traditionally been used as the unmarked gender and have been claimed to be inclusive of all genders. While the Royal Spanish Academy (RAE) rejects the use of inclusive language and thus deems all variables of inclusion of double gender as unnecessary, the vast majority of universities are promoting not only inclusive language but also gender-inclusive curricula. Adopting gender-fair language policies and including gender perspective in the curricula is an innovative trend at university level and in primary and secondary school education. Inclusion in education is a basic human right and the foundation for a more just and equal society. Educators can facilitate the process of welcoming by ensuring handbooks, forms, and other communications are inclusive of all family structures and gender identities. Using gendered language such as 'girls and boys' can be alienating for gender non-conforming and gender diverse students; on the other hand, non-gendered words like 'students' are regarded as inclusive of all identities. The paper discusses the results of mixed method research (survey, interviews, and experiment) conducted in Rainbow and non-Rainbow schools in Alacant and Barcelona (Spain). The experiment aimed at checking the role of gender-fair language in learners' perception of gender balance. It was conducted in Spanish, Catalan, and English. Students aged 10 to 16 (N > 600) were asked to draw pictures of people using specific prompts. The prompts in Spanish and Catalan were written using the generic masculine, 'los presidentes' 'els presidents' (presidents); using double gendered language such as 'ninos y ninas', 'nens i nenes' (boys and girls); and using non-gendered words like 'alumnado' 'alumnat' (students). The prompts were subdivided into people in school contexts participants could identify with, such as students and teachers; occupations mostly associated with men, such as pilots and firefighters; and occupations associated with women, such as ballet dancers and nurses. As could be expected, the participants only drew approximately the same percentage of female and male characters when double-gendered language or non-gendered words such as 'students' or 'teachers' were used, regardless of the language used in the experiment. When they were asked to draw people using the so-called generic masculine in Spanish or Catalan, 'los estudiantes' 'els estudiants' (students), less than 35% of the drawings contained female characters. The differences between the results for Rainbow and Non-Rainbow schools will be discussed in the light of the innovative coeducation programmes and learners' perceptions on gender-fair language gathered in the surveys and interviews.

Keywords: gender-fair language, gender-inclusive schools, learners’ and teachers’ perceptions and attitudes, rainbow coeducation programmes

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Authors: Joy Aworo-Okoroh

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Literary texts are mirrors of a real-life situation. Thus, authors choose the linguistic items that would best encode their intended meanings and messages. However, words mean more than they seem. The meaning of words is not static rather, it is dynamic as they constantly enter into relationships within a context. Literary texts can only be meaningful if all pragmatic cues are identified and interpreted. Drawing upon Teun Van Djik's theory of local pragmatic coherence, it is established that words enter into relations in a text and these relations account for sequential speech acts in the texts. Comprehension of the text is dependent on the interpretation of these relations.To show the relevance of pragmatic coherence in literary text analysis, ten conversations were selected in Americanah in order to give a clear idea of the pragmatic relations used. The conversations were analysed, identifying the speech act and epistemic relations inherent in them. A subtle analysis of the structure of the conversations was also carried out. It was discovered that justification is the most commonly used relation and the meaning of the text is dependent on the interpretation of these instances' pragmatic coherence. The study concludes that to effectively teach literature in English, pragmatic coherence should be incorporated as words mean more than they say.

Keywords: pragmatic coherence, epistemic coherence, speech act, Americanah

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Authors: D. K. Kumador, E. A. Muthivhi

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Historically, reforms in early childhood education in Ghana have focused narrowly on structural and pedagogical aspects with little attention paid to the broader sociocultural framework within which schooling and child development systems interact. This preliminary study investigates inclusive early childhood education within rapidly changing Ghanaian socio-cultural context, and its consequences for the development of children with learning disabilities. The study addresses an important topic, which is largely under-researched outside of Europe, North America, and Australasia. While inclusive education has been widely accepted globally at the level of policy, its implementation is uneven, as is shown in numerous studies across an array of countries and education systems. Despite this burgeoning area of research internationally, there have been far fewer studies conducted in African settings and fewer still that use cultural-historical activity theory as an investigative approach. More so, specific literature on the subject in the Ghanaian context is non-existent and, as such, coming to a deeper understanding of the sociocultural practices that shape, and possibly impede, inclusive early childhood education in an African country, Ghana, is a worthwhile research endeavour. Using cultural-historical activity theory as a methodological framework, this study employed classroom observations, and in-depth interviews and focus group discussions of preschool teachers in three kindergarten centres in the Greater Accra Region of Ghana to qualitatively explore inclusive early childhood education and the development of children with learning disabilities. The findings showed that literature from Ghana rarely discusses child informed consent as an on-going process that must be articulated throughout the research process from data collection to analysis, reporting and dissemination. Further, the study showed that the introduction and implementation of inclusive education framework – with its concomitant revisions in the curriculum, policies, and school rules, as well as enhanced community and parent involvement – into existing schooling practices, generated contradictions in inclusive teachers’ approaches to teaching and learning, and classroom management. Generally, contradictions in the understanding and acceptability of approaches to teaching and learning occur when a new way of doing things is incorporated into existing practices. These contradictions are thought to be a source of change and development. Thus, they guide teachers to unlearn outmoded practices, relearn or learn new approaches that are beneficial to the development of all children. Nonetheless, the findings of the current study showed that preschool teachers’ belief systems and perceptions of disabilities mediated the outcomes of such contradictions. Also, that was evidenced in the way they engaged children with learning disabilities compared to their typically developing counterparts, showing disregard for what was prescribed by new policies and school rules. The findings have implications for research with young children and the development outcomes of children with learning disabilities in inclusive early childhood education settings.

Keywords: CHAT, classroom management, cultural-historical activity theory, ghana, inclusive early childhood education, schooling practices, young children with learning disabilities

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Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

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Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: Alimohamad Asghari, Ahmad Daneshi, Mohammad Farhadi, Arash Bayat, Mohammad Ajalloueyan, Marjan Mirsalehi, Mohsen Rajati, Seyed Basir Hashemi, Nader Saki, Ali Omidvari

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Evidence suggests that Cochlear Implantation (CI) is a beneficial approach for auditory and speech skills improvement in children with severe to profound hearing loss. However, it remains controversial if implantation in children <12 months is safe and effective compared to older children. The present study aimed to determine whether children's ages affect surgical complications and auditory and speech development. The current multicenter study enrolled 86 children who underwent CI surgery at <12 months of age (group A) and 362 children who underwent implantation between 12 and 24 months of age (group B). The Categories of Auditory Performance (CAP) and Speech Intelligibility Rating (SIR) scores were determined pre-impanation, and "one-year" and "two-year" post-implantation. Four complications (overall rate: 4.65%; three minor) occurred in group A and 12 complications (overall rate: 4.41%; nine minor) occurred in group B. We found no statistically significant difference in the complication rates between the groups (p>0.05). The mean SIR and CAP scores improved over time following CI activation in both groups. However, we did not find significant differences in CAP and SIR scores between the groups across different time points. Cochlear implantation is a safe and efficient procedure in children younger than 12 months, providing substantial auditory and speech benefits comparable to children undergoing implantation at 12 to 24 months of age. Furthermore, surgical complications in younger children are similar to those of children undergoing the CI at an older age.

Keywords: cochlear implant, Infant, complications, outcome

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Authors: Rabab M. Ramadan, Elaraby A. Elgallad

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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)

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Authors: Sadeq Al Yaari, Fayza Al Hammadi, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari, Salah Al Yami

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Background: When we further take Arabic grammatical issues into account in accordance with applied linguistic investigations on Arabic as Second Language (ASL) learners, a fundamental issue arises at this point as to the production of speech in Arabic: Oral grammatical errors committed by ASL learners. Aims: Using manual rating as well as computational analytic methodology to test a corpus of recorded speech by Second Language (ASL) learners of Arabic, this study aims to find the areas of difficulties in learning Arabic grammar. More specifically, it examines how and why ASL learners make grammatical errors in their oral speech. Methods: Tape recordings of four (4) Arabic as Second Language (ASL) learners who ranged in age from 23 to 30 were naturally collected. All participants have completed an intensive Arabic program (two years) and 20 minute-speech was recorded for each participant. Having the collected corpus, the next procedure was to rate them against Arabic standard grammar. The rating includes four processes: Description, analysis and assessment. Conclusions: Outcomes made from the issues addressed in this paper can be summarized in the fact that ASL learners face many grammatical difficulties when studying Arabic word order, tenses and aspects, function words, subject-verb agreement, verb form, active-passive voice, global and local errors, processes-based errors including addition, omission, substitution or a combination of any of them.

Keywords: grammar, error, oral, Arabic, second language, learner, applied linguistics.

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Authors: Tashwill Esterhuizen

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Throughout Africa, several countries continue to have laws which criminalise same-sex sexual activities, which increases the vulnerability of the LGBT community to stigma, discrimination, and persecution. These criminal provisions often form the basis upon which states deny LGBT activists the right to freely associate with other like-minded individuals and form organizations that protect their interests and advocate for the rights and aspirations of the LGBT community. Over the past year, however, there has been significant progress in the advancement of universal, fundamental rights of LGBT persons throughout Africa. In many instances, these advancements came about through the bravery of activists who have publically insisted (in environments where same-sex sexual practices are criminalised) that their rights should be respected. Where meaningful engagement with the State was fruitless, activists took their plight to the judiciary and have successfully sought to uphold the fundamental rights of LGBT persons, paving the way for a more inclusive and tolerant society. Litigation Progress: Botswana is a prime example. For several years, the State denied a group of LGBT activists their right to freely associate and form their organisation Lesbians, Gays, and Bisexuals of Botswana (LEGABIBO), which aimed to promote the interests of the LGBT community in Botswana. In March 2016, the Botswana Court of Appeal found that the government’s refusal to register LEGABIBO violated the activists’ right to associate freely. The Court held that the right freedom of association applies to all persons regardless of their sexual orientation or gender identity. It does not matter that the views of the organisation are unpopular or unacceptable amongst the majority. In particular, the Court rejected the government of Botswana’s contention that registering LEGABIBO would disturb public peace and is contrary to public morality. Quite remarkably, the Court of Appeal recognised that while LGBT individuals are a minority group within the country, they are nonetheless persons entitled to constitutional protections of their dignity, regardless of whether they are unacceptable to others on religious or any other grounds. Furthermore, the Court held that human rights and fundamental freedoms are granted to all, including criminals or social outcasts because the denial of an individual’s humanity is the denial of their human dignity. This is crucial observation by the Court of Appeal, as once it is accepted that human rights apply to all human beings, then it becomes much easier for vulnerable groups to assert their own rights. Conclusion: The Botswana Court of Appeal decision, therefore, represents significant progress in the promotion of the rights of lesbian, gay, bisexual and transgender persons. The judgment has broader implications for many other countries which do not provide recognition of sexual minorities. It highlights the State’s duty to uphold basic rights and to ensure dignity, tolerance, and acceptance for marginalised persons.

Keywords: acceptance, freedom of association, freedom of expression, fundamental rights and freedoms, gender identity, human rights are universal, inclusive, inherent human dignity, progress, sexual orientation, tolerance

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Authors: Abdullah A. AlShaher

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In this paper, we demonstrate how regression curves can be used to recognize 2D non-rigid handwritten shapes. Each shape is represented by a set of non-overlapping uniformly distributed landmarks. The underlying models utilize 2^nd order of polynomials to model shapes within a training set. To estimate the regression models, we need to extract the required coefficients which describe the variations for a set of shape class. Hence, a least square method is used to estimate such modes. We then proceed by training these coefficients using the apparatus Expectation Maximization algorithm. Recognition is carried out by finding the least error landmarks displacement with respect to the model curves. Handwritten isolated Arabic characters are used to evaluate our approach.

Keywords: character recognition, regression curves, handwritten Arabic letters, expectation maximization algorithm

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Authors: Thuy Bui Anh, Ngan Nguyen Thi Thanh

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Currently, social work in Vietnam is entering the first step in the development process to become a true profession with a strong position in society. However, Spirit of helping and sharing of social work has already existed in the daily life of Vietnamese people for a very long time, becoming a precious heritage passed down from ancestors to the next generations while expanding the territory, building and defending for the country. Following the stream of history, charity work in Vietnam has gradually transformed itself towards a more professional work, especially in the last 2 decades. Accordingly, more than 50 universities and educational institutions in Vietnam have been licensed to train social work, ensuring a stronger foundation on human resources working in this field. Despite the strong growth, social work profession, social work education and the recognition of the role of the social workers still need to be fueled to develop, responded to the increasing demand of Vietnam society.

Keywords: education, history, recognition, social work, Vietnam

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Fathimath Warda, Mariyam Nihaadh

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Students with Special Education Needs (SEN) are increasing in the Maldives, like anywhere else in the world, due to the changes in lifestyle of the people and ease of being diagnosed with advancements in medical health. With the growth in the population of these students, the demand for professionals in various fields is unmet. Thus, with the introduction of the Inclusive Education Policy in 2013, all students are educated in the same classroom by the regular teacher. This poses problems as the teachers are not well trained and qualified to meet the varying needs of the students, given the limited time and the large number of students in the classroom. This is a major concern for all stakeholders in the education sector and research has been conducted by various local scholars in this area. However, studies on the role of parents of such students is an area that remains yet to be explored in the Maldives, which makes a study of this nature crucial. The main aim of this study is to determine the ways in which the education provided to Special Needs Students can be maximized for a better outcome. Therefore, the study intends to understand the involvement of parents in providing education to special needs students from the teachers' perspectives. The basis for this study is the Parent Development Theory developed by Mowder, which was initially known as Parent Role Development Theory. A qualitative research has thus been utilised for the purpose of the study as it requires to find the beliefs and attitudes of teachers, along with relevant justifications regarding the role of parents in educating students with special needs. Data was gathered using one-to-one interviews, as it is one of the most reliable ways of getting meaningful and in-depth data. The study employs a total of 8 participants who are teachers teaching in inclusive classes where students with special needs are included. Emphasis was paid to select teachers who have the experience of teaching students with different disorders commonly found in the Maldives, namely in the four areas, Autism Spectrum Disorder, Down Syndrome, Attention Deficit Hyperactive Disorder and speech impairment. Hence, purposive sampling will be used to select the participants. Data analysis has been done using thematic coding. The findings revealed that teachers highlighted that parents' involvement was a key factor in ensuring success of education in children with special needs. Thus, the study concludes that the role of parents as a necessary input for the proper development of children and in educating children with special needs, suggesting that extra measures have to be taken develop a positive relationship between teachers and parents in order to strengthen this aspect.

Keywords: involvement, parents' role, special education needs, teachers' voice

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Authors: L. Horňák

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The aim of the paper is to analyze a longstanding problem in Slovakia – the effective education of Roma students coming from socially disadvantaged backgrounds. Although it is a relatively small country, there are over 630 communities in the Slovak Republic. The efficiency of the projects was verified by interviews with participants; questionnaires; and direct observations. Evaluation reports which summarized and evaluated the outcomes of the projects only confirmed their success. Slovakia realizes that appropriate social inclusion of marginalized citizens coming from the Roma ethnic group can only be achieved through education based on equality of all students and acceptance of diversity.

Keywords: inclusive education, marginalized communities, Roma pupil, equity in education, socially disadvantaged backgrounds, social inclusion

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio Velastin

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We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from color video sequences. Our approach proceeds along two stages. In the first, we run a real-time 2D pose detector to determine the precise pixel location of important key points of the body. A two-stream neural network is then designed and trained to map detected 2D keypoints into 3D poses. In the second, we deploy the Efficient Neural Architecture Search (ENAS) algorithm to find an optimal network architecture that is used for modeling the Spatio-temporal evolution of the estimated 3D poses via an image-based intermediate representation and performing action recognition. Experiments on Human3.6M, Microsoft Research Redmond (MSR) Action3D, and Stony Brook University (SBU) Kinect Interaction datasets verify the effectiveness of the proposed method on the targeted tasks. Moreover, we show that our method requires a low computational budget for training and inference.

Keywords: human action recognition, pose estimation, D-CNN, deep learning

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Authors: Rasha Salameh

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In light of the tense relationship between Saudi Arabia and Iran, this research paper sheds some light on Al-Arabiya’s reporting of Coronavirus in the Gulf. Particularly because most of the cases, in the beginning, were coming from Iran, some programs of this Saudi channel embraced a conspiracy theory. Hate speech has been used in talking about the topic and discussing it. The results of these discussions will be detailed in this paper in percentages with regard to the research sample, which includes five programs on Al-Arabiya channel: ‘DNA’, ‘Marraya’ (Mirrors), ‘Panorama’, ‘Tafaolcom’ (Your Interaction) and the ‘Diplomatic Street’, in the period between January 19, that is, the date of the first case in Iran, and April 10, 2020. The research shows the use of a conspiracy theory in the programs, in addition to some professional violations. The surveyed sample also shows that the matter receded due to the Arab Gulf states' preoccupation with the successively increasing cases that have appeared there since the start of the pandemic. The results indicate that hate speech was present in the sample at a rate of 98.1% and that most of the programs that dealt with the Iranian issue under the Corona pandemic on Al Arabiya used the conspiracy theory at a rate of 75.5%.

Keywords: Al-Arabiya, Iran, Corona, hate speech, conspiracy theory, politicization of the pandemic

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Authors: Manuela S. Tolentino, John G. Nepomuceno

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The purpose of this investigation was to assess the implementation of inclusive education (IE) in 6 elementary and 5 secondary public schools in the City Schools Division of Dasmarinas. Participants in this study were 11 school heads, 73 teachers, 22 parents and 22 students (regular and with special needs) who were selected using purposive sampling. A 30-item questionnaire was used to gather data on the extent of the implementation of IE in the division while focus group discussion (FGD) was used to gather insights on what facilitate and hinder the implementation of the IE program. This study assessed the following variables: school culture and environment, inclusive education policy implementation, and curriculum design and practices. Data were analyzed using frequency count, mean and ranking. Results revealed that participants have similar assessment on the extent of the implementation of IE. School heads rated school culture and environment as highest in terms of implementation while teachers and pupils chose curriculum design and practices. On the other hand, parents felt that inclusive education policies are implemented best. School culture and environment are given high ratings. Participants perceived that the IE program in the division is making everyone feel welcome regardless of age, sex, social status, physical, mental and emotional state; students with or without disability are equally valued, and students help each. However, some aspects of the IE program implementation are given low ratings namely: partnership between staff, parents and caregivers, school’s effort to minimize discriminatory practice, and stakeholders sharing the philosophy of inclusion. As regards education policy implementation, indicators with the highest ranks were school’s effort to admit students from the locality especially students with special needs, and the implementation of the child protection policy and anti-bullying policy. The results of the FGD revealed that both school heads and teachers possessed the welcoming gesture to accommodate students with special needs. This can be linked to the increasing enrolment of SNE in the division. However, limitations of the teachers’ knowledge on handling learners, facilities and collaboration among stakeholders hinder the implementation of IE program. Based on the findings, inclusion program framework was developed for program enhancement. This will be the basis for the improvement of the program’s efficiency, the relationship between stakeholders, and formulation of solutions.

Keywords: inclusion, inclusive education, framework, special education

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Authors: Shantanu Arya, Sachin Sakhuja, Gunjan Mehta, Sanjay Munjal

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Stuttering may be defined as a speech disorder affecting the fluency domain of speech and characterized by covert features like word substitution, omittance and circumlocution and overt features like prolongation of sound, syllables and blocks etc. Many etiologies have been postulated to explain stuttering based on various experiments and research. Moreover, Breathlessness has also been reported by many individuals with stuttering for which breathing exercises are generally advised. However, no studies reporting objective evaluation of the pulmonary capacity and further objective assessment of the efficacy of breathing exercises have been conducted. Pulmonary Function Test which evaluates parameters like Forced Vital Capacity, Peak Expiratory Flow Rate, Forced expiratory flow Rate can be used to study the pulmonary behavior of individuals with stuttering. The study aimed: a) To identify speech motor & physiologic behaviours associated with stuttering by administering PFT. b) To recognize possible reasons for an association between speech motor behaviour & stuttering severity. In this regard, PFT tests were administered on individuals who reported signs and symptoms of stuttering and showed abnormal scores on Stuttering Severity Index. Parameters like Forced Vital Capacity, Forced Expiratory Volume, Peak Expiratory Flow Rate (L/min), Forced Expiratory Flow Rate (L/min) were evaluated and correlated with scores of Stuttering Severity Index. Results showed significant decrease in the parameters (lower than normal scores) in individuals with established stuttering. Strong correlation was also found between degree of stuttering and the degree of decrease in the pulmonary volumes. Thus, it is evident that fluent speech requires strong support of lung pressure and requisite volumes. Further research in demonstrating the efficacy of abdominal breathing exercises in this regard is needed.

Keywords: forced expiratory flow rate, forced expiratory volume, forced vital capacity, peak expiratory flow rate, stuttering

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Authors: Maha Jazouli

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Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

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Authors: Sotiria Tzivinikou, Dimitra Kagkara

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Teacher’s sense of self-efficacy can affect significantly both teacher’s and student’s performance. More specific, self-efficacy is associated with the learning outcomes as well as student’s motivation and self-efficacy. For example, teachers with high sense of self-efficacy are more open to innovations and invest more effort in teaching. In addition to this, effective inclusive education is associated with higher levels of teacher’s self-efficacy. Pre-service teachers with high levels of self-efficacy could handle student’s behavior better and more effectively assist students with special educational needs. Teacher preparation programs are also important, because teacher’s efficacy beliefs are shaped early in learning, as a result the quality of teacher’s education programs can affect the sense of self-efficacy of pre-service teachers. Usually, a number of pre-service teachers do not consider themselves well prepared to work with students with special educational needs and do not have the appropriate sense of self-efficacy. This study aims to investigate the factors that contribute to the improvement of the sense of self-efficacy of pre-service special educators by using an academic practicum training program. The sample of this study is 159 pre-service special educators, who also participated in the academic practicum training program. For the purpose of this study were used quantitative methods for data collection and analysis. Teacher’s self-efficacy was assessed by the teachers themselves with the completion of a questionnaire which was based on the scale of Teacher’s Sense of Efficacy Scale. Pre and post measurements of teacher’s self-efficacy were taken. The results of the survey are consistent with those of the international literature. The results indicate that a significant number of pre-service special educators do not hold the appropriate sense of self-efficacy regarding teaching students with special educational needs. Moreover, a quality academic training program constitutes a crucial factor for the improvement of the sense of self-efficacy of pre-service special educators, as additional for the provision of high quality inclusive education.

Keywords: inclusive education, pre-service, self-efficacy, training program

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Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

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Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

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Authors: Seham El Kareh, Miramar Etman

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Recently, detecting liars and extracting features which distinguish them from truth-tellers have been the focus of a wide range of disciplines. To the author’s best knowledge, most of the work has been done on facial expressions and body gestures but only few works have been done on the language used by both liars and truth-tellers. This paper sheds light on four axes. The first axis copes with building an audio corpus for deceptive and truthful speech for Egyptian Arabic speakers. The second axis focuses on examining the human perception of lies and proving our need for computational linguistic-based methods to extract features which characterize truthful and deceptive speech. The third axis is concerned with building a linguistic analysis program that could extract from the corpus the inter- and intra-linguistic cues for deceptive and truthful speech. The program built here is based on selected categories from the Linguistic Inquiry and Word Count program. Our results demonstrated that Egyptian Arabic speakers on one hand preferred to use first-person pronouns and present tense compared to the past tense when lying and their lies lacked of second-person pronouns, and on the other hand, when telling the truth, they preferred to use the verbs related to motion and the nouns related to time. The results also showed that there is a need for bigger data to prove the significance of words related to emotions and numbers.

Keywords: Egyptian Arabic corpus, computational analysis, deceptive features, forensic linguistics, human perception, truthful features

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Authors: Senait G. Worku, Ellen Mangnus

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Inclusive business models which integrates low-income people with companies value chain in a commercially viable way has gained momentum for the perceived potential to contribute to poverty alleviation and food security in developing countries. This article investigates the impact of Community Revenue Enhancement through Technology Extension (CREATE) project of Heineken brewery on smallholder farmers’ wellbeing in Arsi zone Oromia regional state of Ethiopia. CREATE is a Public-Private Partnership (PPP) between Ministry of Foreign Affairs of the Netherlands and Heineken N.V. which source malt barely from smallholder farmers in three zones of Oromia. The study assessed the impact of CREATE on malt barley productivity, food security and new asset purchase in Arsi zone by comparing households that participate in the project with non-participating households using propensity score matching method. The finding indicated that households that participated in the CREATE project had higher malt barley productivity and purchased more new assets than non-participating households. However, there is no significant difference on food security status of participating and non-participating households indicating that the project has a profound impact on asset accumulation than on food security improvement.

Keywords: inclusive business, malt barley, propensity score matching, wellbeing

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Montaha Al Yaari, Ayman Al Yaari, Aayah Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Introduction: It is well established that lengthening (longer duration) is considered one of the correlates of lexical and phrasal prominence. However, it is unexplored whether the scope of vowel lengthening in the Arabic dialect of Yemen (ADY) is differently affected by educated and/or uneducated speakers from different dialectal backgrounds. Specifically, the research aims to examine whether or not linguistic background acquired through different educational channels makes a difference in the speech of the speaker and how that is reflected in related psychoneurolinguistic impairments. Methods: For the above mentioned purpose, we conducted an articulatory experiment wherein a set of words from ADY were examined in the dialectal speech of thousand and seven hundred Yemeni educated and uneducated speakers aged 19-61 years growing up in five regions of the country: Northern, southern, eastern, western and central and were, accordingly, assigned into five dialectal groups. A seven-minute video clip was shown to the participants, who have been asked to spontaneously describe the scene they had just watched before the researchers linguistically and statistically analyzed recordings to weigh vowel lengthening in the speech of the participants. Results: The results show that vowels (monophthongs and diphthongs) are lengthened by all participants. Unexpectedly, educated and uneducated speakers from northern and central dialects lengthen vowels. Compared with uneducated speakers from the same dialect, educated speakers lengthen fewer vowels in their dialectal speech. Conclusions: These findings support the notion that extensive exposure to dialects on account of standard language can cause changes to the patterns of dialects themselves, and this can be seen in the speech of educated and uneducated speakers of these dialects. Further research is needed to clarify the phonemic distinctive features and frequency of lengthening in other open class systems (i.e., nouns, adjectives, and adverbs). Phonetic and phonological report measures are needed as well as validation of existing measures for assessing phonemic vowel length in the Arabic population in general and Arabic individuals with voice, speech, and language impairments in particular.

Keywords: vowel lengthening, Arabic dialect of Yemen, phonetics, phonology, impairment, distinctive features

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

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Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: pollen recognition, logistic model tree, expectation-maximization, local binary pattern

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Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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Authors: Zuzanna Miodonska, Michal Krecichwost, Pawel Badura

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Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems.

Keywords: computer-aided pronunciation evaluation, sigmatism diagnosis, speech signal analysis, statistical verification

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