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Deep learning approach for natural language processing, speech, and computer vision : techniques and use cases
\"Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of natural language processing (NLP), Speech and Computer Vision tasks. It simplifies and presents the concepts of deep learning in a comprehensive manner, with suitable, full-fledged examples of deep learning models, with aim to bridge the gap between the theoretical and the applications using case studies with code, experiments, and supporting analysis. Features: Covers latest developments in deep learning techniques as applied to audio analysis, computer vision, and Natural Language Processing Introduces contemporary applications of deep learning techniques as applied to audio, textual, and visual processing Discovers deep learning frameworks and libraries for NLP, Speech and Computer vision in Python Gives insights into using the tools and libraries in python for real-world applications. Provides easily accessible tutorials, and real-world case studies with code to provide hands-on experience. This book is aimed at researchers and graduate students in computer engineering, image, speech, and text processing\"-- Provided by publisher.
BOOK
Measuring Students’ Use of Zoom Application in Language Course Based on the Technology Acceptance Model (TAM)
The study uses technology acceptance model (TAM) to gain insights into user reactions to the technology adopted for language learning. The study aims to analyze the correlation between the variables of TAM on using Zoom application in language learning, in addition to examining how gender and experience influence the use of technology. The participants of this study comprise of 75 undergraduate English-as-Foreign-Language learners who have studied for their courses online during the COVID-19 pandemic. The results of the study reveal a strong positive correlation between the actual use of Zoom and the students’ attitudes and behavioral intention. In addition, there is a positive correlation between computer self-efficacy and other variables (i.e. PU, actual use, PEU, attitude and behavioral intention). Further, while the results reveal that there is no correlation between the gender and any variables of the model, it has been found that experience is positively correlated with the variables of TAM.
Journal Article
Educational AI Chatbots for Content and Language Integrated Learning
Using advanced artificial intelligence (AI) technology in learning environments is one of the latest challenges for educators and education policymakers. Conversational AI brings new possibilities for alternative and innovative Information and Communication Technologies (ICT) tools, such as AI chatbots. This paper reports on field experiments with an AI chatbot and provides insights into its contribution to Content and Language Integrated Learning (CLIL). More specifically, this paper presents an experimental use case of an educational AI chatbot called AsasaraBot, designed to teach high school students cultural content in a foreign language, i.e., English or French. The content is related to the Minoan Civilization, emphasizing the characteristic figurine of the Minoan Snake Goddess. The related chatbot-based educational program has been evaluated at public and private language schools in Greece. The findings from these experiments show that the use of AI chatbot technology for interactive ICT-based learning is suitable for learning foreign languages and cultural content at the same time. The AsasaraBot AI chatbot has been designed and implemented in the context of a postgraduate project using open-source and free software.
Journal Article
Deep learning with applications using Python : chatbots and face, object, and speech recognition with TensorFlow and Keras
Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models and algorithms required for deep learning applications.
Book
Technology in Language Use, Language Teaching, and Language Learning
This article offers a capacious view of technology to suggest broad principles relating technology and language use, language teaching, and language learning. The first part of the article considers some of the ways that technological media influence contexts and forms of expression and communication. In the second part, a set of heuristic questions is proposed to help guide language teachers and researchers in determining how to incorporate technology into their teaching practice or research agenda and evaluate its suitability and impact. These questions are based primarily on the goal of helping learners to pay critical attention to the culturally encoded connections among forms, contexts, meanings, and ideologies that they will encounter and produce in different mediums, both traditional and new.
Journal Article
The effectiveness of app‐based language instruction for developing receptive linguistic knowledge and oral communicative ability
Hundreds of millions of language learners around the globe study a second language with popular apps such as Duolingo, Rosetta Stone, Busuu, and Babbel. This study examined the effectiveness of one app, Babbel, for developing both receptive linguistic knowledge of vocabulary and grammar, as well as oral communicative ability in Spanish as a second language. Fifty‐four English speakers not enrolled in Spanish classes studied Spanish on Babbel over the course of 12 weeks, with a goal of studying roughly 10 min per day. Participants completed pretests and posttests, and provided data on their motivation to learn Spanish and use Babbel. Results showed that learners were able to develop grammar and vocabulary knowledge as well as oral communicative ability. The amount of Babbel study time was the strongest predictor for all three measures, with motivation to learn Spanish also significantly predicting growth in oral communicative ability. The Challenge Hundreds of millions of learners use digital apps to learn world languages, but how effective are these apps for learning how to speak a second language? To answer this question, this article compares the grammar, vocabulary, and speaking development of 54 learners who spent three months studying Spanish with the app Babbel.
Journal Article
Mobile-assisted language learning: A Duolingo case study
The growing availability of mobile technologies has contributed to an increase in mobile-assisted language learning in which learners can autonomously study a second language (L2) anytime or anywhere (e.g. Kukulska-Hulme, Lee & Norris, 2017; Reinders & Benson, 2017). Research investigating the effectiveness of such study for L2 learning, however, has been limited, especially regarding large-scale commercial L2 learning apps, such as Duolingo. Although one commissioned research study found favorable language learning outcomes (Vesselinov & Grego, 2012), limited independent research has reported issues related to learner persistence, motivation, and program efficacy (Lord, 2015; Nielson, 2011). The current study investigates the semester-long learning experiences and results of nine participants learning Turkish on Duolingo. The participants showed improvement on L2 measures at the end of the study, and results indicate a positive, moderate correlation between the amount of time spent on Duolingo and learning gains. In terms of perceptions of their experiences, the participants generally viewed Duolingo’s flexibility and gamification aspects positively; however, variability in motivation to study and frustration with instructional materials were also expressed.
Journal Article