MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202641071565 A) filed by Dr V Ponnulexmi; T. D. Mary Binu; V. R. Rojar Benz; and Asha Selva Jeni. P on June 09, 2026, for Ai Enabled Developing Spoken Fluency Through Task-Based Teaching.
Inventors include Dr V Ponnulexmi; T. D. Mary Binu; V. R. Rojar Benz; and Asha Selva Jeni. P.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: AI ENABLED DEVELOPING SPOKEN FLUENCY THROUGH TASK-BASED TEACHING ABSTRACT: The integration of Artificial Intelligence (AI) into language learning and instruction has garnered significant attention in educational research, particularly with the enhancement of speaking skills. Despite the exciting potential of AI-powered solutions to mitigate Foreign Language Anxiety (FLA), enhance self-regulated learning, and deliver personalised instruction, empirical research on their impact on practical language acquisition remains sparse. This will examine the possibilities of AI-assisted language tools in addressing these difficulties and enhancing speaking competency. The principal aim of acquiring a second language is to facilitate communication in both written and oral forms. Acquiring proficiency in a target language necessitates instruction and training utilising tactics and approaches that students should master at the collegiate level. Nevertheless, some colleges inadequately provide instruction to enhance students' speaking skills. The instruction and acquisition of English have predominantly focused on reading and writing skills, rather than on listening and speaking skills. Proficient verbal communication is essential for advanced education and professional opportunities. The current curriculum, instructional techniques, and resources must be developed with consideration for the necessity of oral proficiency in English. There should be a focus on enhancing the assessment of students' speaking proficiency and oral fluency at the collegiate level. EFL learners engaged in self-directed study encounter ongoing fluency difficulties, especially when opportunities to interact with native speakers or instructors are restricted. Recent breakthroughs in generative AI present disruptive promise by emulating human-like interactions and accommodating individual learner requirements. This study examines how AI specifically enhances speaking fluency using Task-Based Learning in self-directed learning and its effect on students' speaking performance.
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