A Review of Accent-Based Automatic Speech Recognition Models for E-Learning Environment

The adoption of electronics learning (e-learning) as a method of disseminating knowledge in the global educational system is growing at a rapid rate, and has created a shift in the knowledge acquisition methods from the conventional classrooms and tutors to the distributed e-learning technique that enables access to various learning resources much more conveniently and flexibly. However, notwithstanding the adaptive advantages of learner-centric contents of e-learning programmes, the distributed e-learning environment has unconsciously adopted few international languages as the languages of communication among the participants despite the various accents (mother language influence) among these participants. Adjusting to and accommodating these various accents has brought about the introduction of accents-based automatic speech recognition into the e-learning to resolve the effects of the accent differences. This paper reviews over 50 research papers to determine the development so far made in the design and implementation of accents-based automatic recognition models for the purpose of e-learning between year 2001 and 2021. The analysis of the review shows that 50% of the models reviewed adopted English language, 46.50% adopted the major Chinese and Indian languages and 3.50% adopted Swedish language as the mode of communication. It is therefore discovered that majority of the ASR models are centred on the European, American and Asian accents, while unconsciously excluding the various accents peculiarities associated with the less technologically resourced continents

Development of Lecture Attendance System for Staff Performance Rating in a Tertiary Institution using Fingerprint Technology

Managing time attendance of staff in organizations has proven to be a challenging endeavor. Manual methods have been proposed in capturing employees’ attendance but there are inadequacies in measuring the performance of employees. This paper aims at promoting staff efficiency at work by developing a secure attendance management system for use in tertiary institutions via two subsystems; Fingerprint biometrics as a method of identification and authentication and Question-Answering module for staff performance rating. The system uses staff fingerprints stored in the database upon registration for carrying out the process of attendance and validate staff lectures’ requirements. It is accentuated by creating a question-answering module that allows students to answer some questions on each available and registered staff, hence, giving a more concentrated content about staff’s activities within the school. The evaluation was carried out based on the matching efficiency and attendance accuracy of the proposed system. The proposed system performed excellently with 98.51% attendance accuracy based on the high successful staff identification recorded. Hence, staff performance rating was generated, thereby creating an avenue for determining promotion grounds