Using Voice Technologies to Support Disabled People

In recent years, significant strides have been made in speech and speaker recognition systems, owing to the rapid evolution of data processing capabilities. Utilizing a speech recognition system facilitates straightforward and efficient interaction, especially for individuals with disabilities. This article introduces an automatic speech recognition (ASR) system designed for seamless adaptation across diverse platforms. The model is meticulously described, emphasizing clarity and detail to ensure reproducibility for researchers advancing in this field. The model’s architecture encompasses four stages: data acquisition, preprocessing, feature extraction, and pattern recognition. Comprehensive insights into the system’s functionality are provided in the Experiments and Results section. In this study, an ASR system is introduced as a valuable addition to the advancement of educational platforms, enhancing accessibility for individuals with visual disabilities. While the achieved recognition accuracy levels are promising, they may not match those of certain commercial systems. Nevertheless, the proposed model offers a cost-effective solution with low computational requirements. It seamlessly integrates with various platforms, facilitates straightforward modifications for developers, and can be tailored to the specific needs of individual users. Additionally, the system allows for the effortless inclusion of new words in its database through a single recording process

Public housing self-selection through user satisfaction in the City of Qom, Iran

This research is focusing on the concept of self-selection, a decision-making process grounded in self-concept, which currently receives less attention in housing provision in Iran. This is an effort to explore new suggestions for improving the level of user satisfaction for future living environments that are designed based on current architectural ideas. Achievement of self-selection is indicated by satisfaction in decision-making process. Therefore, the aim of this research is to enhance general housing satisfaction in Qom, Iran by improving the level of residential satisfaction of public housings through the decision making process for future designs. The objectives of this research are to investigate the attributes of the residential environment, related to user self-selection of public housings in Qom, and to measure the residential satisfaction level of public housings through various aspects of self-selection. Sequential mixed methods were employed based on post-occupancy evaluation questionnaire, which clarify the level of user satisfaction. The survey questionnaire was administered to a sample (N=109) of Iranian residents who live in the public housing of Mehr Projects in the Pardisan area of Qom. The collected data were processed with IBM SPSS, ANOVA, and Smart-PLS for frequency, t-tests and model testing. The results indicate that the mean score for user residential satisfaction, self-selection and overall quality of future design are above neutral. The findings suggest that the respondents were satisfied with their current experience of living in the apartments. The quality of current state of the building has improved, and the quality of future design needs less improvement. The results can be useful in assisting architects to predict residential satisfaction and subsequently consider the desired level of self-selection in their design process. In conclusion, the significant determinants of user satisfaction by different attributes of self-selection have been highlighted, and the findings show the central position of self-selection in architectural design

Designing for disability: Guidance for designers when working with users with Specific, Critical, Additional Needs (SCAN)

This study provides guidelines to help designers make reasoned methodological choices when working with those that have disabilities, in order to enable the effective interpretation of the views of these users and to ensure that these are taken into account in the design of products and services. A new way of categorising such users led to a definition by the researcher of Specific, Critical, Additional Needs (SCAN). Individuals with SCAN have additional needs that have to be met in order to maintain their quality of life, health, safety and wellbeing but are additional to those of everyday critical needs. Following an extensive review of models of disability and design, together with the legal and social contexts (including public attitudes to disability), as well as resources from the design and ergonomics communities and existing research methods available to designers when working with SCAN users, it was found that there were relatively few studies that examined the appropriateness of methods for understanding the requirements of these users in design and evaluation processes. Through focus groups, advice was gathered from designers, some of whom were experienced in working collaboratively with disabled persons. Following this, several semi-structured interviews took place with a representative sample of SCAN users, carers, support workers, health and social care professionals and family members. Analysis of these interviews, backed by evidence from the literature, led to the creation of guidelines. The guidelines take account of best practice in designing from a user-centred viewpoint, and a number of tried and tested research methods are reviewed in detail. The study also highlights the range of disabilities that should be considered by designers in shaping specifications for new products and services, and the need to treat users appropriately to ensure an accurate account is taken of their needs

On Data-driven systems analyzing, supporting and enhancing users’ interaction and experience

Tesis doctoral en inglés y resumen extendido en español[EN] The research areas of Human-Computer Interaction and Software Architectures have been traditionally treated separately, but in the literature, many authors made efforts to merge them to build better software systems. One of the common gaps between software engineering and usability is the lack of strategies to apply usability principles in the initial design of software architectures. Including these principles since the early phases of software design would help to avoid later architectural changes to include user experience requirements. The combination of both fields (software architectures and Human-Computer Interaction) would contribute to building better interactive software that should include the best from both the systems and user-centered designs. In that combination, the software architectures should enclose the fundamental structure and ideas of the system to offer the desired quality based on sound design decisions. Moreover, the information kept within a system is an opportunity to extract knowledge about the system itself, its components, the software included, the users or the interaction occurring inside. The knowledge gained from the information generated in a software environment can be used to improve the system itself, its software, the users’ experience, and the results. So, the combination of the areas of Knowledge Discovery and Human-Computer Interaction offers ideal conditions to address Human-Computer-Interaction-related challenges. The Human-Computer Interaction focuses on human intelligence, the Knowledge Discovery in computational intelligence, and the combination of both can raise the support of human intelligence with machine intelligence to discover new insights in a world crowded of data. This Ph.D. Thesis deals with these kinds of challenges: how approaches like data-driven software architectures (using Knowledge Discovery techniques) can help to improve the users' interaction and experience within an interactive system. Specifically, it deals with how to improve the human-computer interaction processes of different kind of stakeholders to improve different aspects such as the user experience or the easiness to accomplish a specific task. Several research actions and experiments support this investigation. These research actions included performing a systematic literature review and mapping of the literature that was aimed at finding how the software architectures in the literature have been used to support, analyze or enhance the human-computer interaction. Also, the actions included work on four different research scenarios that presented common challenges in the Human-Computer Interaction knowledge area. The case studies that fit into the scenarios selected were chosen based on the Human-Computer Interaction challenges they present, and on the authors’ accessibility to them. The four case studies were: an educational laboratory virtual world, a Massive Open Online Course and the social networks where the students discuss and learn, a system that includes very large web forms, and an environment where programmers develop code in the context of quantum computing. The development of the experiences involved the review of more than 2700 papers (only in the literature review phase), the analysis of the interaction of 6000 users in four different contexts or the analysis of 500,000 quantum computing programs. As outcomes from the experiences, some solutions are presented regarding the minimal software artifacts to include in software architectures, the behavior they should exhibit, the features desired in the extended software architecture, some analytic workflows and approaches to use, or the different kinds of feedback needed to reinforce the users’ interaction and experience. The results achieved led to the conclusion that, despite this is not a standard practice in the literature, the software environments should embrace Knowledge Discovery and data-driven principles to analyze and respond appropriately to the users’ needs and improve or support the interaction. To adopt Knowledge Discovery and data-driven principles, the software environments need to extend their software architectures to cover also the challenges related to Human-Computer Interaction. Finally, to tackle the current challenges related to the users’ interaction and experience and aiming to automate the software response to users’ actions, desires, and behaviors, the interactive systems should also include intelligent behaviors through embracing the Artificial Intelligence procedures and techniques

On data-driven systems analyzing, supporting and enhancing users’ interaction and experience

[EN]The research areas of Human-Computer Interaction and Software Architectures have been traditionally treated separately, but in the literature, many authors made efforts to merge them to build better software systems. One of the common gaps between software engineering and usability is the lack of strategies to apply usability principles in the initial design of software architectures. Including these principles since the early phases of software design would help to avoid later architectural changes to include user experience requirements. The combination of both fields (software architectures and Human-Computer Interaction) would contribute to building better interactive software that should include the best from both the systems and user-centered designs. In that combination, the software architectures should enclose the fundamental structure and ideas of the system to offer the desired quality based on sound design decisions. Moreover, the information kept within a system is an opportunity to extract knowledge about the system itself, its components, the software included, the users or the interaction occurring inside. The knowledge gained from the information generated in a software environment can be used to improve the system itself, its software, the users’ experience, and the results. So, the combination of the areas of Knowledge Discovery and Human-Computer Interaction offers ideal conditions to address Human-Computer-Interaction-related challenges. The Human-Computer Interaction focuses on human intelligence, the Knowledge Discovery in computational intelligence, and the combination of both can raise the support of human intelligence with machine intelligence to discover new insights in a world crowded of data. This Ph.D. Thesis deals with these kinds of challenges: how approaches like data-driven software architectures (using Knowledge Discovery techniques) can help to improve the users' interaction and experience within an interactive system. Specifically, it deals with how to improve the human-computer interaction processes of different kind of stakeholders to improve different aspects such as the user experience or the easiness to accomplish a specific task. Several research actions and experiments support this investigation. These research actions included performing a systematic literature review and mapping of the literature that was aimed at finding how the software architectures in the literature have been used to support, analyze or enhance the human-computer interaction. Also, the actions included work on four different research scenarios that presented common challenges in the Human- Computer Interaction knowledge area. The case studies that fit into the scenarios selected were chosen based on the Human-Computer Interaction challenges they present, and on the authors’ accessibility to them. The four case studies were: an educational laboratory virtual world, a Massive Open Online Course and the social networks where the students discuss and learn, a system that includes very large web forms, and an environment where programmers develop code in the context of quantum computing. The development of the experiences involved the review of more than 2700 papers (only in the literature review phase), the analysis of the interaction of 6000 users in four different contexts or the analysis of 500,000 quantum computing programs. As outcomes from the experiences, some solutions are presented regarding the minimal software artifacts to include in software architectures, the behavior they should exhibit, the features desired in the extended software architecture, some analytic workflows and approaches to use, or the different kinds of feedback needed to reinforce the users’ interaction and experience. The results achieved led to the conclusion that, despite this is not a standard practice in the literature, the software environments should embrace Knowledge Discovery and datadriven principles to analyze and respond appropriately to the users’ needs and improve or support the interaction. To adopt Knowledge Discovery and data-driven principles, the software environments need to extend their software architectures to cover also the challenges related to Human-Computer Interaction. Finally, to tackle the current challenges related to the users’ interaction and experience and aiming to automate the software response to users’ actions, desires, and behaviors, the interactive systems should also include intelligent behaviors through embracing the Artificial Intelligence procedures and techniques

Improving accessibility for people with dementia: web content and research

The Internet can provide a means of communication, searching for information, support groups and entertainment, amongst other services, and as a technology, can help to promote independence for people with dementia. However, the effectiveness of this technology relies on the users’ ability to use it. Web content, websites and online services need to be designed to meet the abilities and needs of people with dementia, and thus the difficulties that these users encounter must be explored and understood.The primary aim of this thesis is to investigate web content accessibility for People with Dementia and develop recommendations for improving current guidelines based on accessibility needs. The secondary aim is to support people with dementia having a voice within research through development of accessible ethical processes.Qualitative data were collected with a scoping study using questionnaires about everyday technology use (people with dementia and older adults without dementia); and in-depth interviews to explore difficulties and web accessibility issues. A document analysis was conducted on Web Content Accessibility Guidelines (ISO/IEC40500:2012) for inclusion of the needs of people with dementia followed by review of Web Usability Guidance (ISO9241-151:2008) to consider how gaps relating to the unmet accessibility needs for people with dementia could be met. The scoping study found that both people with dementia and older adults without dementia use everyday ICT to access the Web. Both groups described difficulties with web interface interactions, which refined the research scope to web content accessibility. The interview data with people with dementia (n=16) and older adults without dementia (n=9) were analysed using Grounded Theory techniques. It was found that both user groups experienced the same types of difficulties using the Web, but that dementia symptoms could exacerbate the difficulties from usability issues (older adults without dementia) into accessibility issues for people with dementia. Navigation was a key issue for both groups, with a range of web content design elements contributing to accessibility issues with navigation for people with dementia. The document analysis found that the accessibility guidance did not address all the accessibility issues encountered by people with dementia. However, the usability guidance did address many of the accessibility issues for web content navigation experienced by people with dementia. The research provides recommendations for improvements to web content accessibility guidelines including content from usability guidelines, and amendments to current guidelines and success criteria. A new ethical recruitment/consent process was developed and tested as part of the research process and is recommended for use in future research to support engagement of people with dementia.</div