Critical Computer Applications in Language Learning

Computer applications in language learning are important and indispensable to today's language learner. This situation is due to the emergence and utility of the software and infinite information sources on the Web, which in a way help learners learn in a more efficient and efficient manner. In addition, in Malaysia, the government emphasizes the knowledge of computer technology among domestic students and educators through the Ministry of Education, Culture, Sports, Science and Technology, and supports the achievement and success of the learning process by maximizing the utility of computer technology doing.

Machine learning has long been established as a field, but recent hype and media attention is mainly due to machine learning applications in the AI ​​field such as computer vision, speech recognition, and language processing. Many of them were first introduced by technology giants like Google, Facebook, Microsoft. Machine learning - Daily software engineering | Jeff interviews the core character of weekly data science. It gives you a very rare early event in Silicon Valley to help you develop new technologies and techniques. It gives you a lot of new ideas to accomplish your work. This is not recommended

Natural language processing and speech recognition is the first commercial application of machine learning. Please follow other automatic recognition tasks (mode, text, sound, image, video, face etc). Applications such as autonomous vehicles, medical diagnostics, games, search engines, spam filtering, crime prevention, marketing, robotics engineering, remote sensing, computer vision, transportation, music recognition, classification etc. explosively expanded ... Artificial intelligence Integrated technology We are using it. It is not currently seen as "AI" to many people, it is merely an expansion of computing. Let's ask people on the street, if they have an AI on their phone they may refuse. However, the AI ​​algorithm can be seen everywhere, from predictive text to camera autofocus system. It is generally thought that artificial intelligence has not arrived yet. But it was there now, and that has passed for a while

Advancement of machine learning and deep learning has accelerated the application of AI in two major fields. First, the rapid development of artificial intelligence technology such as computer vision, NLP, speech recognition. These advances are the foundation of artificial intelligence development. It is because you can capture and interpret raw sensations and language inputs for a wide range of uses using computers. Next, both companies and start-ups have deployed these improved features in a variety of applications and industries including autonomous vehicles, retail, sales / customer support, healthcare, financial services, and others. The following figure shows the development of AI technology and shows some examples of applications that support AI.