# Context-Based Model for Browsing the Web Through Voice
## 9 Limitations and Future Work  
Throughout this research, the following limitations were found:  
* Android's security policies on microphone use and recording present challenges for continuous speech recognition. The native service limits recognition duration, impacting continuous use and multimodal interface performance, and blocking the user interface in some cases. Additionally, microphone activation must occur in the foreground, disrupting content playback, especially for audio and video, making it impossible to simulate continuous recognition by toggling the microphone on and off;
* Websites implement security measures such as robots.txt files, dynamic JavaScript, CAPTCHA challenges, and automation limits to protect their resources. While these measures are essential for security, they hinder static analysis methods such as those used in our prototype. During testing, platforms such as YouTube and Amazon temporarily blocked the device's IP, limiting access to content and interfering with contextual analysis;
* Stanford CoreNLP, a tool used in web content analysis, lacks optimization for resource-constrained mobile devices, requiring a remote server installation, which adds dependency and increases latency.  
In the development and evaluation of our proposal, several aspects to be improved were revealed:  
* Improve the clarity of information messages presented to the user;
* Develop a new strategy for continuous speech recognition by optimizing phrase detection and filtering environmental noise;* Find, optimize, or develop tools that enable the model to operate independently without relying on other devices, since in the current configuration, there is a dependency on the device running the Stanford CoreNLP server;
* Integrate transformers to generate natural language responses from web page content, reducing the need for extensive reading and providing users with search-relevant information;
* Develop additional prototypes using a user-centered design methodology, that incorporates continuous evaluation and user feedback to improve adaptability and efficiency in real-world environments;
* Address website security limitations by developing advanced strategies to handle obstacles like CAPTCHA challenges, optimizing robots.txt file processing, and managing dynamic scripts. Additionally, explore approaches that comply with security policies, while ensuring access to relevant content for voice browsing;
* Expand the Web Page Context Analyzer component to incorporate a semantic and dynamic analysis of web page structure and content;
* Incorporate additional navigation functionalities into web pages, which is directly related to the previous point. This expansion in browsing capabilities will contribute to improving usability by providing more complete and specific options in the interaction with web content;
* Use free software tools to implement speech-to-text and text-to-speech components, reducing costs and promoting a more sustainable solution.  
Conceptualization, C.S.A.M. and J.G.R.G.; methodology, C.S.A.M. and J.G.R.G.; software, C.S.A.M.; validation, C.S.A.M.; formal analysis, C.S.A.M. and J.G.R.G.; investigation, C.S.A.M.; resources, J.G.R.G., S.M. and D.D.; data curation, C.S.A.M.; writing--original draft preparation, C.S.A.M. and S.M.; writing--review and editing, J.G.R.G., S.M. and D.D.; visualization, S.M. and D.D.; supervision, J.G.R.G.; project administration, D.D. All authors have read and agreed to the published version of the manuscript.  
[PERSON] Avalos Montiel thanks the Consejo Nacional de Humanidades, Ciencias y Tecnologias (Conahcyt) for the grant number 4022959.  
The data presented in this study are available on request from the corresponding authors. The data are not publicly available due to privacy reasons.  
The authors declare no conflicts of interest.