# Context-Based Model for Browsing the Web Through Voice
## 1 Introduction  
According to [PERSON] \"...ubiquitous computing makes technology help people to live in the real world...\" [1]. However, most people who work closely with information and communications technologies (ICTs) use visual interfaces that force them to pay attention to the input and output devices used and that, in some cases, require certain skills to perform a specific task, e.g., web browsing. In web browsing, the visual mode continues to predominate for the delivery and selection of content. For this activity, hypertext documents and a browser or viewer on the user's device are needed. In the browser, the user must select the links they wish to follow and, in the same way, the user must read and interpret which pages or websites are most useful, discarding those that are not interesting for them [2, 3]. In recent years, the use of virtual assistants such as Amazon Alexa, Google Assistant, or Siri has become popular. These assistants receive user requests through voice commands and allow actions similar to web browsing such as playing music, performing searches, creating shopping lists, controlling smart electronic devices, and setting alarms. However, the availability of these actions depends on the applications installed in the assistants [4, 5, 6, 7]. Assistive technology, such as JAWS [8], VoiceOver [9], WebReader [10], SRAA [11], and Hearsay [12], has been developed for visually impaired people to navigate the Web. These proposals work in environments composed of desktop computers or laptops and input peripherals, such as braille keyboards, microphones, or computer mice. They receive instructions using combinations of keys, screen gestures, or specific voice commands and deliver content to users using audio or braille. There are even browser extensions, such as iTOC [13] and SaIL [14], for the JAWS screen reader that help find information that is considered relevant through statistical or semantic analysis of web pages, with the goal of reducing the time spent browsing the Web. Despite the increase in the use of ICTs, there are individuals who are excluded from the benefits and opportunities that these technologies offer. The existence of this digital divide not only reflects a disparity in access to information but also contributes to marked social inequality [15]. One of the reasons why the digital divide occurs is due to the lack of user skills, motivations, or attitudes necessary to operate ICTs. This problem may be due to illiteracy or the inability to carry out an action at a certain time. Thus, the need to address the digital divide arises. The development of voice interfaces in virtual assistants, screen readers, and chatbots plays an important role in simplifying interaction and helping to combat the digital divide. However, these solutions have significant limitations in web browsing. For example, some chatbots are designed exclusively for a specific website or area, and virtual assistants cannot navigate web pages, restricting their usefulness in this specific task. In addition, those solutions that can browse the Web do not guarantee to effectively retrieve information regarding the user's intentions and interests. To obtain the most suitable results, users should use search strategies [16], e.g., defining filters, configuring the web browser, and using Boolean operators and special characters. These strategies can be complicated for a user without the right skills. For these reasons, a proposal that transforms the digital experience for those who face significant barriers in the information age becomes relevant. In this paper, we propose a model to facilitate web browsing by calculating the coincidences between the user's context and that of the web pages to deliver content oriented to the user's interests.