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the framework of the digital economy, the need to be able to learn a language effectively
                  increased significantly. English is now the universal communication and business language,
                  as well as academic and electronic communication. Consequently, ESL learners will have
                  to acquire effective linguistic competencies, especially in knowledge of vocabulary and
                  accuracy of pronunciation so that they can effectively communicate in global contexts.
                  The acquisition of vocabulary can be regarded as one of the most basic components of
                  second language learning since this process has a direct impact on the capability of the
                  learner to comprehend the text, convey ideas, and engage in any meaningful
                  communication (Nation, 2013). In the event that learners lack adequate vocabulary
                  knowledge, then they might not understand the spoken or written language regardless of
                  having a good idea of the structures of grammar. On the same note, pronunciation is a
                  key element in a second language communication. Proper pronunciation assists learners
                  to express themselves well, and it also makes their speech to be understood by others.
                  Lack of good pronunciation on the other hand, can cause misunderstandings and
                  breakdown in communication. The conventional method of teaching pronunciation is
                  prone to chances of using teacher demonstration and repetition which might not offer an
                  adequate individualized feedback to students. New opportunities in the field of
                  pronunciation training can be realized by the AI-based technologies that offer immediate
                  corrective feedback and enable the learners to repeatedly practice in an autonomous
                  learning environment, especially through the use of automatic speech recognition (ASR)
                  systems (Liakin, Cardoso, and Liakina, 2015). The recent phase in application of AI has
                  brought in numerous intelligent learning systems which facilitate the learning of a second
                  language. An example is that intelligent tutoring systems can scan the progress of the
                  learners and adjust the instructional contents according to their unique needs and
                  performance rates. Equally, natural language processing technologies can be used to
                  analyze the language usage of the learners and give recommendations on how to improve
                  it. These characteristics assist in designing a more interactive and individualized teaching
                  setting, which is also crucial to efficient language acquisition (Holmes, Bialik, and Fadel,
                  2019). Moreover, AI tools are capable of assisting learners in training language skills out
                  of the classroom, therefore, encouraging autonomous learning and constant involvement
                  with the language. Empirical studies have shown that AI technologies are effective in
                  language teaching more and more often. Research has revealed that AI-based learning
                  environments have the potential to greatly enhance vocabulary acquisition in learners
                  through the provision of contextualized learning resources, interactive activities as well as
                  adaptive feedback systems (Godwin-Jones, 2019). Also, AI-based pronunciation aids can
                  enable learners to obtain an in-depth feedback on the pronunciation mistakes to enhance
                  their phonetic accuracy and fluency in speaking. The technologies also minimise the
                  anxiety that learners have when it comes to speaking in a second language since they
                  enable the students to practice in their own time and privacy. The other significant
                  benefit of AI-based language learning systems is that it can be used to enable customized
                  learning. The common challenges in traditional language classrooms can be categorized
                  as the large number of students in the classroom, a lack of learning time, and varying
                  levels of student proficiency. These aspects render the instructors unable to give
                  personalized attention to each student. This limitation is resolvable with the help of AI
                  technologies that examine the progress of learners and modify learning activities based
                  on the analysis outcomes. Zawacki-Richter et al. (2019) state that AI-based educational
                  systems can have a revolutionary impact on higher education as they allow creating


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