A Software Engineered Voice-Enabled Job Recruitment Portal System

The inability of job seekers to get timely job information regarding the status of the application submitted via conventional job portal system which is usually dependent on accessibility to the Internet has made so many job applicants to lose their placements. Worse still, the epileptic services offered by Internet Service Providers and the poor infrastructures in most developing countries have greatly hindered the expected benefits from Internet usage. These have led to cases of online vacancies notifications unattended to simply because a job seeker is neither aware nor has access to the Internet. With an increasing patronage of mobile phones, a self-service job vacancy notification with audio functionality or an automated job vacancy notification to all qualified job seekers through mobile phones will simply provide a solution to these challenges. In this paper, we present a Voice-enabled Job Recruitment Portal (JRP) System. The system is accessed through two interfaces – the voice user’s interface (VUI) and web interface. The VUI was developed using VoiceXML and the web interface using PHP, and both interfaces integrated with Apache and MySQL as the middleware and back-end component respectively. The JRP proposed in this paper takes the hassle of job hunting from job seekers, provides job status information in real-time to the job seeker and offers other benefits such as, cost, effectiveness, speed, accuracy, ease of documentation, convenience and better logistics to the employer in seeking the right candidate for a job

A FRAMEWORK FOR INTELLIGENT VOICE-ENABLED E-EDUCATION SYSTEMS

Although the Internet has received significant attention in recent years, voice is still the most convenient and natural way of communicating between human to human or human to computer. In voice applications, users may have different needs which will require the ability of the system to reason, make decisions, be flexible and adapt to requests during interaction. These needs have placed new requirements in voice application development such as use of advanced models, techniques and methodologies which take into account the needs of different users and environments. The ability of a system to behave close to human reasoning is often mentioned as one of the major requirements for the development of voice applications. In this paper, we present a framework for an intelligent voice-enabled e-Education application and an adaptation of the framework for the development of a prototype Course Registration and Examination (CourseRegExamOnline) module. This study is a preliminary report of an ongoing e-Education project containing the following modules: enrollment, course registration and examination, enquiries/information, messaging/collaboration, e-Learning and library. The CourseRegExamOnline module was developed using VoiceXML for the voice user interface(VUI), PHP for the web user interface (WUI), Apache as the middle-ware and MySQL database as back-end. The system would offer dual access modes using the VUI and WUI. The framework would serve as a reference model for developing voice-based e-Education applications. The e-Education system when fully developed would meet the needs of students who are normal users and those with certain forms of disabilities such as visual impairment, repetitive strain injury (RSI), etc, that make reading and writing difficult

A Voice-Enabled Framework for Recommender and Adaptation Systems in E-Learning

With the proliferation of learning resources on the Web, finding suitable content (using telephone) has become a rigorous task for voice-based online learners to achieve better performance. The problem with Finding Content Suitability (FCS) with voice E-Learning applications is more complex when the sight-impaired learner is involved. Existing voice-enabled applications in the domain of E-Learning lack the attributes of adaptive and reusable learning objects to be able to address the FCS problem. This study provides a Voice-enabled Framework for Recommender and Adaptation (VeFRA) Systems in E-learning and an implementation of a system based on the framework with dual user interfaces – voice and Web. A usability study was carried out in a visually impaired and non-visually impaired school using the International Standard Organization’s (ISO) 9241-11 specification to determine the level of effectiveness, efficiency and user satisfaction. The result of the usability evaluation reveals that the prototype application developed for the school has “Good Usability” rating of 4.13 out of 5 scale. This shows that the application will not only complement existing mobile and Web-based learning systems, but will be of immense benefit to users, based on the system’s capacity for taking autonomous decisions that are capable of adapting to the needs of both visually impaired and non-visually impaired learners

Development of Telephone-based e-Learning Portal

The proliferation of mobile phones in Nigeria, particularly among the student community, has continued to inspire the development and delivery of e-Learning applications. Most of the existing web-based e-Learning applications do not support nomadic voice-based learning (i.e. learning on the move through voice), and consequently do not provide a speedy access to information or enquiries on demand. Internet access is required to get every bit of information from most school portal system, which is not directly available to everyone. Lack of provision for voice in the existing web applications excludes support for people with limited capabilities such as the visually impaired and physical disabilities. In this paper, we present a design and development of a prototype telephone-based e-Learning portal that will be used for course registration and examination. This study is part of an ongoing e-Learning project involving the following modules: enrollment, course registration and examination, enquiries/information, messaging/collaboration, e-Learning and library. The prototype application was developed using VoiceXML for the voice user interface(VUI), PHP for database queries, Apache as the middle-ware and MySQL database as back-end. A unified modelling language (UML) was used to model and design the application. The proposed e-Learning system will compliment the web-based system in other to meet the needs of students with a range of disabilities such as visual impairment, repetitive strain injury, etc, that make reading and writing difficult. It also makes multiple platforms available to all users as well as boosting access to education for the physically challenged, particularly the sight impaired in the developing countries of the world. In institutions where students are not allowed to use mobile phones or where cost is an issue, then the alternative is the use of PC-phone

A Case-Based Reasoning Approach for Speech-Enabled e-Learning System

E-Learning plays an important role in our society today; hence, higher institutions now offer courses through distance learning. Several studies and methodologies towards improving e-Learning have been proposed and provided. However, not too many works are dedicated to the design and implementation of e-Learning for the visually impaired learners. Sight challenge is a serious form of disability, yet, the existing e-Learning platform (web, mobile, etc) have not devoted enough attention to the plight of the visually impaired particularly in the area of usability. The objective of this paper is to present an intelligent speech-based e-Learning system with dual interface – Voice User Interface (VUI) and Web User Interface (WUI). Case-Based Reasoning (CBR) was engaged to provide intelligent services. Voice Extensible Markup Language (VoiceXML) was used to develop the VUI, Hypertext Preprocessor (PHP) for the WUI and Apache as the middle ware. The VUI and WUI are accessed through mobile phone by dialing a telephone number and the WUI using the Internet respectively. The e-Learning system will especially be useful for students who are visually impaired and those with dyslexia ailment that make reading, writing and spelling difficult. The application will complement the existing e-Learning systems such as web-based learning, m-Learning and others

A Voice-based Mobile Prescription Application for Healthcare Services (VBMOPA)

Adverse drug effects are a major cause of death in the world with tens of thousand deaths occurring across the world each year because of medication or prescription errors. Many of such errors involve the administration of the wrong drug or dosage by care givers to patients due to indecipherable handwritings, drug interactions, confusing drug names etc. The adoption of voice-based mobile applications could eliminate some of these errors because they allow prescription information to be captured and heard through voice response rather than in the physician’s handwriting. This paper presents a design and implementation of a Voice-based Mobile Prescription Application (vbmopa) to improve health care services. The application can be accessed through a mobile phone by dialing an appropriate number. This system could lead to costs and life savings in healthcare centres across the world especially in developing countries where treatment processes are usually cumbersome and paper based

Deep Item-based Collaborative Filtering for Top-N Recommendation

Item-based Collaborative Filtering(short for ICF) has been widely adopted in recommender systems in industry, owing to its strength in user interest modeling and ease in online personalization. By constructing a user's profile with the items that the user has consumed, ICF recommends items that are similar to the user's profile. With the prevalence of machine learning in recent years, significant processes have been made for ICF by learning item similarity (or representation) from data. Nevertheless, we argue that most existing works have only considered linear and shallow relationship between items, which are insufficient to capture the complicated decision-making process of users. In this work, we propose a more expressive ICF solution by accounting for the nonlinear and higher-order relationship among items. Going beyond modeling only the second-order interaction (e.g. similarity) between two items, we additionally consider the interaction among all interacted item pairs by using nonlinear neural networks. Through this way, we can effectively model the higher-order relationship among items, capturing more complicated effects in user decision-making. For example, it can differentiate which historical itemsets in a user's profile are more important in affecting the user to make a purchase decision on an item. We treat this solution as a deep variant of ICF, thus term it as DeepICF. To justify our proposal, we perform empirical studies on two public datasets from MovieLens and Pinterest. Extensive experiments verify the highly positive effect of higher-order item interaction modeling with nonlinear neural networks. Moreover, we demonstrate that by more fine-grained second-order interaction modeling with attention network, the performance of our DeepICF method can be further improved.Comment: 25 pages, submitted to TOI