Natural Language Processing (NLP) technology has come a long way in the past few years. Applications are becoming accessible to more and more users. In the era of digital transformation of enterprises, this is great for speedy and simple application development. Natural Language Conversational User Interfaces (NL-CUI) have become an important leap in the convergence of AI (Artificial Intelligence) and frontend. A conversational user interface (CUI) uses speech recognition and speech generation to create an interface with the user, in which the user may speak with the computer using ordinary language, rather than predetermined commands.
CUIs alleviate the limitations of conventional software solutions that do not support verbal interaction. For example, interacting with an application is often restricted to pressing limited buttons and uttering simple, standard phrases to request information. This is far from offering a natural and pleasant interaction with computer applications, especially when computer illiterate, elderly and disabled users are involved. Hence, conversational UIs that support voice and verbal input can be a great addition when it comes to interactions with front end applications like virtual assistants or chatbots. The latter are becoming ubiquitous in a wide array of sectors including banking, e-commerce, retail, and healthcare. Specifically, conversational UIs enable organizations to expand their front-end service capacity, which helps organization achieve ambitious operational excellence goals.
In several cases conversational UIs are also enhanced with inclusive features that support the interaction of elderly and disabled users. However, designing conversational and inclusive UI technologies requires a great effort to ensure that the way your app talks with a user and the information that is conveyed in the conversation are made in a flexible way. This requires the use of proper design techniques and the deployment of novel digital technologies.
Building a conversational user interface is a complex UI/UX design process that requires not just technical expertise but also an understanding of how humans interact with each other. The first step to building a conversational UI is to design conversations that are appropriate for the context and situation in which they will be used. This includes identifying the needs of users, the tasks they want to accomplish, and how they want these tasks performed. When designing these conversations, it’s important to keep in mind that people tend to respond better when they feel like they are being spoken to as an equal rather than as an inferior or superior.
To ensure the development of an ergonomic, pleasant, and easy to use conversational UI, it is important to research into people’s behaviors and preferences in order to understand their motivations, desires and needs. This research also helps identify gaps between what users are currently doing in order to achieve their goals and what is possible within the application’s capabilities.
Once you have identified what users need from your application, you can begin designing potential solutions that use human-to-human communication patterns rather than computer-to-human. Additionally, designers of conversational UIs must consider how non-native speakers will use their product. An interface that is clear and easy for native English speakers may be confusing or difficult for non-native speakers who speak other languages or dialects.
Inclusive conversational UIs must also comply with accessibility standards like WCAG (Web Content Accessibility Guidelines), which is a key to ensuring inclusiveness. WCAG is a set of standards that define how to make web content more accessible to people who have disabilities. In general, the most common way for developers to ensure that their applications are accessible is by using a checklist at each stage of development (design, code, test). However, in some cases it might be worthwhile to test your application against WCAG requirements directly and look for issues before you get started on development. Beyond WCAG compliance, developers of inclusive conversational UIs must ensure their interfaces are accessible and usable by everyone, including people with disabilities, seniors and children, who may have different needs than most users of the product. In this direction, they must include diverse voices as part of the development team, including diverse individuals in terms of age, gender, race, and ethnicity. Such diversity should be part of a co-creation process that engages different stakeholders in the design, development, deployment, and testing of the inclusive conversational UI. A main outcome of such a co-creation process is a positive user experience that is respectful of other human beings. Moreover, inclusive conversational UIs should inclusive language in all parts of the product or service.
From a technological perspective, the creation of a conversation UI is typically based on a chatbot that can understand natural language and respond accordingly. This technology is called NLP and uses advanced algorithms to recognize human speech and extract meaning from it. Most chatbots interact with users through multiple channels such as text messages, voice commands, or in-app messaging systems.
In recent years, there are also conversational UIs based on more sophisticated bots that support spoken dialogue interactions. These bots use voice recognition technology to detect spoken words in order to engage with users in real time. Moreover, the bots that support spoken dialogue are able to maintain the context of a conversation across different phrases. This enables end-users to interact with bots that offer human-like conversational capabilities. Likewise, this makes it very difficult for humans to understand that they speak to a computer and not to a human agent. Emerging Artificial Intelligence (AI) regulations like the AI Act in Europe are likely to oblige operators of such systems to inform users that they interact with an AI system rather than with a human officer.
Apart from AI technology, conversational UIs leverage cloud computing. Cloud computing provides the resources needed for developing conversational UIs. The main advantage of cloud computing is that it allows developers to use all computational resources available within a network, which means they can build complex applications without worrying about the computational resources needed to execute the NLP applications. Overall, the cloud helps enterprises improve their operational capabilities in a cost-effective way.
Another technology that plays a significant role in the development and deployment of conversational UIs is mobile computing. Mobile devices have become an integral part of our lives and people use them every day for different purposes such as making phone calls, sending emails or text messages, browsing the Internet, etc. Nowadays, many chatbots are offered through mobile devices such as smartphones, which broadens the base of users that interact with conversational UIs. For instance, many conversational UIs are offered through popular mobile channels such as Facebook Messenger on mobile.
Overall, inclusive conversional UIs provide a host of benefits to service developers and operators that opt to offer them to their users. Specifically, they can be used in a variety of situations and contexts, including mobile devices and websites. In most cases they are quite easy to create, as they can be developed without a lot of programming knowledge beyond basic HTML and CSS skills. Moreover, they’re intuitive and easy to use for end-users, which boosts the operational efficiency of their IT applications. Through conversational UIs users don’t have to learn complex commands or procedures before they can start interacting with a system. Most importantly, when developed with inclusive features they facilitate elderly, disabled and other handicapped users to use them. For all these reasons, applications developers should consider the chatbots and spoken dialogue interaction as part of their digital transformation strategies.
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