ADAPTIVE SPEECH TECHNOLOGIES AND LEARNER AUTONOMY: REIMAGINING ENGLISH PRONUNCIATION THROUGH ARTIFICIAL INTELLIGENCE

Artificial Intelligence (AI) is rapidly reshaping language education, with adaptive speech technologies standing out as a pivotal innovation for pronunciation training. Using automated speech recognition (ASR) and deep learning, these tools deliver instant, individualized feedback that strengthens learners’ accuracy, fluency, and confidence. This paper synthesizes evidence from global empirical studies alongside emerging African applications to identify consistent pedagogical gains, including improved pronunciation accuracy, increased learner autonomy, and higher engagement in self-regulated learning. Building on this synthesis, the paper demonstrates how tools such as ELSA Speak, Google Read Along, and Speech Ace can be pedagogically integrated into English pronunciation teaching in Tanzania. The analysis shows that these technologies align strongly with the communicative ambitions of the Competence-Based Curriculum (CBC) and offer practical solutions for overcrowded, resource-limited classrooms. The paper further identifies the institutional actors responsible for effective alignment, namely the Ministry of Education, Science and Technology (MoEST), the Tanzania Institute of Education (TIE), and teacher-training institutions, each tasked with policy guidance, curriculum adaptation, and teacher capacity-building. It concludes that when these stakeholders coordinate ethical data governance and localized content development, adaptive speech technologies can serve as a realistic pathway for strengthening English proficiency, enhancing learner autonomy, and widening equitable access to quality pronunciation instruction across Tanzania.