A Systematic Study and Empirical Analysis of Lip Reading Models using Traditional and Deep Learning Algorithms

Despite the fact that there are many applications for analyzing and recreating the audio through existinglip movement recognition, the researchers have shown the interest in developing the automatic lip-readingsystems to achieve the increased performance. Modelling of the framework has been playing a major role inadvance yield of sequential framework. In recent years there have been lot of interest in Deep Neural Networks(DNN) and break through results in various domains including Image Classification, Speech Recognition andNatural Language Processing. To represents complex functions DNNs are used and also they play a vital rolein Automatic Lip Reading (ALR) systems. This paper mainly focuses on the traditional pixel, shape and mixedfeature extractions and their improved technologies for lip reading recognitions. It highlights the mostimportant techniques and progression from end-to-end deep learning architectures that were evolved duringthe past decade. The investigation points out the voice-visual databases that are used for analyzing and trainthe system with the most common words and the count of speakers and the size, length of the language andtime duration. On the flip side, ALR systems developed were compared with their old-style systems. Thestatistical analysis is performed to recognize the characters or numerals and words or sentences in English andcompared their performances

IMPROVED LIP-READING LANGUAGE USING GATED RECURRENT UNITS

Lip-reading is one of the most challenging studies in computer vision. This is because lip-reading requires a large amount of training data, high computation time and power, and word length variation. Currently, the previous methods, such as Mel Frequency Cepstrum Coefficients (MFCC) with Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) with LSTM, still obtain low accuracy or long-time consumption because they use LSTM. In this study, we solve this problem using a novel approach with high accuracy and low time consumption. In particular, we propose to develop lip language reading by utilizing face detection, lip detection, filtering the amount of data to avoid overfitting due to data imbalance, image extraction based on CNN, voice extraction based on MFCC, and training model using LSTM and Gated Recurrent Units (GRU). Experiments on the Lip Reading Sentences dataset show that our proposed framework obtained higher accuracy when the input array dimension is deep and lower time consumption compared to the state-of-the-art

Language and Culture in Northeast India and Beyond: In Honor of Robbins Burling

This volume celebrates the life and work of Robbins Burling, Emeritus Professor of Anthropology and Linguistics at the University of Michigan, giant in the fields of anthropological linguistics, language evolution, and language pedagogy, and pioneer in the ethnography and linguistics of Tibeto-Burmanspeaking groups in the Northeast Indian region. We offer it to Professor Burling – Rob – on the occasion of his 90th birthday, on the occasion of the 60th year of his extraordinary scholarly productivity, and on the occasion of yet another – yet another! – field trip to Northeast India, where his career in anthropology and linguistics effectively began so many decades ago, and where he has amassed so many devoted friends and colleagues – including ourselves. (First paragraph of Editor's Introduction)

Social Transformation toward Sustainable Society

Transformation refers to a dramatic change, which prompts a different form to\ud the new one. In natural science, this is associated with a metamorphosis\ud process, which convert something into a new form or nature. In the context of\ud social science, social transformation refers to social change in dramatic way,\ud while business transformation designates fundamental changes in business\ud way to achieve its specific purposes, such as high level of efficiency, market\ud value or financial sustainability. The study of business and social\ud transformation sheds new light on an important contingency and resourcebased\ud theory, which reveals pathways for continuing research.In emerging economies, social transformation indicates a new wave of\ud development studies, which brings about new concept of sustainable\ud development, followed by sustained superior performance. The capacity of\ud organization to deal with environmental turbulence, such as market,\ud competitiveness, technology and policy plays pivotal role on superior\ud performance and sustainability. This paper discusses the concept of social\ud transformation and sustainable community, which provides challenge for\ud conceptual and empirical research

Learner autonomy: The complexity of control‐shift

It is generally held that constructing learner autonomy (LA) requires a pedagogical shift of control from teachers to students. It is also understood that the development of learner autonomy relates largely to teacher autonomy (TA), which requires school managers to relinquish some degree of control to teachers. However, from a socio‐political perspective, the construct of autonomy is a right also extended to educational managers (MA). Thus, a problem arises: how can the three levels of controlshifts co‐exist and survive in harmony, and ideally, thrive each in its own way? Based on a recent case study, this paper aims to explore the complexity of the dynamic interaction between these three types of autonomy within an educational hierarchy. The study was conducted in a private Chinese secondary school which was promoting whole‐person development through a comprehensive innovation project involving all its academic staff members. The participants comprised nine English teachers, the principal, and the school’s executive director. Data collection was conducted through interviews, classroom observations followed by post‐lesson discussions, and the researcher’s field notes. Specifically, three questions were addressed in this paper focusing on managers’ perceptions of LA, a classroom instruction model intended to cultivate LA, and an in‐house professional development scheme to facilitate TA, all of which impacted on teachers’ professional decision‐making. The findings display a complex picture of these issues, and imply the importance of a genuine shared understanding of the nature of autonomy and the need to carefully ensure the optimal balance among the three types of autonomy in the design and implementation of curriculum innovations

Cognitive load theory and listening to accent variations in English

Accent variability is an emerging field of study in listening to varieties of English. Mutual intelligibility of accent variations in monolingual, as well as multilingual settings may become challenging for native as well as non-native speakers of English. In a CLT framework this thesis examined the accent variability effect and the expertise reversal effect in listening to native and foreign-accented English with different levels of expertise groups. The three experiments reported in this thesis addressed issues of how accent variability boosted meaningful understanding of listening comprehensions, and how instructional design could aide learning in perceptual listening environments so that learners did not become entangled in the novelty of the accents; at the same time maximising the learning of such instructional procedures.In Experiment 1 three single-accent conditions and six multiple-accent conditions were used. The accents were Australian English, Chinese-accented English and Russian-accented English. These three accents were permuted in six combinations to have the six multiple-accent conditions. The results of Experiment 1 did not support the hypotheses. The low expertise learners did not perform better in single-accent conditions and the high expertise learners did not perform better in multiple-accent conditions. In Experiment 2 Russian-accented English and Australian English were employed. The results partially supported the hypotheses. It was found that the single-accent condition was not easier for the low expertise students whereas the dual-accent condition was easier for the high and very high expertise students. In Experiment 3 the low expertise group listening to Indian-accented English found the accent condition easier than the low expertise group listening to both Indian and Arabic-accented English. The high and very high expertise students learned more listening to Arabic and Indian-accented English than listening to Indian-accented English only. The low expertise individuals were more prone to be challenged by the novelty of the dual-accent conditions. The findings of the experiments were explained in terms of accent variability effect and expertise reversal effect in a CLT framework. Instructional design, as pertaining to this thesis facilitated the naïve, as well as expert English language learners’ abilities in extracting accent-independent global adaptation to English within a CLT framework