Chat is the preferred option for most website owners to engage with their visitors. A good reason for this is the non-intrusive nature of text-based communication. It all started with SMS (Short Message Service) as part of the 2G GSM mobile communication technology and the younger generation adopted it quickly. Texting has now become such an ingrained part of our lives that it seems preferable to type a message than saying it. Moreover, this has also morphed into so many mediums of communication, such as Twitter, Whatsapp and off-late the spur of web-based chat apps that leverage the cloud communication technology.
If your website has a global footprint and receives sizable traffic then merely having a chat app may not be enough. You need to cater to the diverse audience from across the world and also be inclusive to their unique needs. In this blog post, we are going to look at three examples of chat app features that can make your offerings stand out from the rest.
If you want to reach out to a global audience, then multilingual support is probably the first thing that you need to implement. Google Translation API is the most preferred choice for language translation. It has the most robust capabilities in terms of accuracy and choice of language. However other players are also catching up by offering translation service as part of their cloud service offerings. Amazon Translate from Amazon and Watson Language Translation service from IBM Cloud are good examples. If you are looking to support language translation to and from a few specific languages, then these might be a better choice. Also concerning pricing, they are slightly cheaper than Google APIs.
Take a look at this screen-cast that shows a demo of on-the-fly translation of chat messages from English to a few other languages.
A multilingual app build with PubNub ChatEngine and Amazon Translate
This app is built using the PubNub ChatEngine and Amazon Translate. PubNub ChatEngine is a framework for building robust chat applications in little time. Riding over PubNub’s robust & real-time data streaming network, ChatEngine does all the heavy lifting of a typical chat application including the sending and delivery of chat messages. Amazon Translate is part of AWS’s AI offering which can perform language translating on short messages as well as large documents. Check out the AWS Translate FAQ page of AWS Translate to know more about the supported languages and other features.
To learn more about developing this chat app, head over to this tutorial.
Accessibility for computer applications is quite often an overlooked consideration during development. A user interface that works for one person might be wholly constrained for a disabled person. Hence designers and developers should empathize with one and all so that we can bring in inclusivity in all our creations. Same things apply to customer interactions as well.
Take the case of a partially blind customer who wants to interact with your website via a chat app. He can type on a tactile keyboard but has to strain his eyes to read text from the screen. Imagine how such a user can benefit from a chat app that supports text to speech conversion feature. Take a look at this video demo to witness this feature.
Chat app with text-to-speech support for incoming message playback
Thanks to Amazon Polly, you can easily convert a text message into an audio clip and stream it back to the application. This demo also leverages the PubNub’s ChatEngine to build the basic chat app with an integrated text to speech streaming feature powered by Amazon Polly.
Check out this blog post to know more about how to build this app with PubNub ChatEngine and Amazon Polly.
If your customers interact with you via chat rooms, then things can quickly get out of hand. The number of messages flowing into public chat rooms can get uncontrollable and beyond a point, it does not add any value to participants. However, this is a considerable amount of data that can be harnessed for a better cause.
The question is how? Take a look at this screen-cast of a public chat room for an epidemic advisory service.
Chat app with automatic data extraction based on location names
Yes, you got the hint. We are talking about generating topics based on location names mentioned in chat messages. Similarly, we can intelligently generate topics based on other types of subjects in the chat messages.
Amazon Comprehend is yet another service from AWS that provides natural language processing capabilities that makes it possible to extract meaningful data from text messages. Yet again, this chat app is built atop the familiar UI interface offered by PubNub ChatEngine. As the chat messages are sent, they are intercepted by PubNub Functions. Each message is then processed through the Amazon Comprehend’s Entity Recognition API to extract the location names. You can take a look at the other features of AWS Comprehend to extract meaningful information from the text.
Here is the blog post with the complete step by step instructions to build the app.
You can also check out some of the previous chat based use cases that we have built using other platforms.
If you are thinking of enhancing the engagement on your chat apps, then it is high time for you to think in the similar lines as shown in the demos above. With Web3.0, apps are getting more and more intelligent, and the same goes for the end user’s expectation. By leveraging the AWS’s services along with the reliability of PubNub, developers can rapidly build cognitive chat applications within no time.
So, if you are building an AI-driven service that can add a spark to chat or messaging apps then let us know. We would love to give it a try and unravel the use cases that can be derived out of it.
Shyam is the Creator-in-Chief at RadioStudio. He is a technology buff and is passionate about bringing forth emerging technologies to showcase their true potential to the world. Shyam guides the team at RadioStudio, a bunch of technoholiks, to imagine, conceptualize and build ideas around emerging trends in information and communication technologies.
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