How AI and Voice Recognition integration can Enhance Application Development?

Personal assistants such as Siri or Cortana or Alexa are becoming more and more popular with smart device users. But not all of them aware the fact that it is the Artificial Intelligent (AI) technology to power them nor the fact that Siri or Cortana are getting smarter and smarter nowadays as they can help provide information, launch services, and answer questions, etc. All is the work of thousands of linguists in collaborate with numerous team of AI and Machine Learning engineers, Data Scientists and app developers as well as various other IT professionals.

This proves that the current labor force in the field of software development is more capable. They could break their own comfort zone and approach to the more sophisticated functions in application development.


Why should app developers use voice integration?

In the initial stages of both iOS and Android, with all the existing fragments, users’ experience was not as satisfying as it is now. Without ecosystem integration, sometimes, app users were required to scroll several applications just to obtain what they really needed. Nowadays, navigability has been dramatically improved with the integration of deep linking into apps. This allows users to function across applications without launching them separately. Facebook app is an example. Its users could at the same time browse information on the new feed, send messages, and take pictures while posting a status without getting out of the app and opening the camera app. Voice is now used to make the navigation process even smoother. With integration of the intelligent voice interfaces, your applications will become an essential part of an increasingly connected mobile ecosystem.

The development of IoT (Internet of Things) is also a reason for voice interface integration. As more things around them get smarter and connected, users do not want to get confused by multiple user device interfaces of their phones, smart watches, smart TVs, or even lights. Then, the need is a universal interface that could unify the interfaces of most or even all devices. And voice interface has emerged as a solution. In most of the smart homes now, people could control most of the devices within their houses using their voice commands. They could turn up or down their TV volume while cooking. Or they even make a phone call to any person in their contact list while driving without any tap of buttons.

Finally, voice interfaces enhance people’s interaction with apps in the most intuitive way: their natural, authentic language. Now, you can command Siri to set an alarm for you at 6:00 a.m. every day by saying natural chunks like “alarms, 6:00 am, and every day” and everything is there ready for you. This process does not require much effort as it used to. This proves that AI has improved the user’s experience and cultivated a stronger connection between apps and users.

Speech recognition becomes smarter.

Making the apps or devices understand your commands and carry them out is the two-step process. Understanding or recognizing the speech from the user is just the first step. Making the speech understood in the required way that AI requires is the other. And many application developers are confused distinguishing the two mentioned steps.

Unifying these two mentioned steps and make them into a success needs the whole process of the following smaller steps:

  • Step 1: Using automatic speech recognition (ASR). This step literally transcribes voice from users to text. Platform such as Android has already provided this capability. But others such as iOS still not. And in case a software development company has a demand to develop their apps on the iOS platform with ASR integration, they have to employ ASR from the third party providers.
  • Step 2: Using natural language understanding (NLU). This step is like a bridge the connect natural language to AI understanding. App Developers provide samples of requests, then machine learning (ML) is used to make the system understand all the requests that are similar to the ones provided. Besides, the system is also aware of contexts, which enable the apps to build more complex interactions and conversations with the users. The open platform even makes this approach more powerful. Thanks to the data contributed to by the developers from the community, AI could be more intelligent understanding more ways of language using of users and their deeper intents.
  • Step 3: Processing the requests. Once the requests of the users are “translated” and made understandable for the AI, developers now could either fulfill the requests in your internal app, or send them to some external services, such as the camera app.

Developers, find your voice

A voice interface will foster your understanding of your users. Voice input isn't only a limited set of buttons and functions. It is also a mean of data collection that helps you easily see exactly what your users are looking for in your app, how they working in your apps, and then could provide accordingly actions. The better understanding of users means better user insight. By working on what your users are requiring on your app now, you can improve revenue with targeted offers and ads.

When the devices are more and more intelligent and users have more satisfying experiences using smart devices, create intuitive experiences on apps tend to be a must for developers. Consumers tend to stay with the pages that provide them with more convenience, they also seek out smart devices with voice integration that make their live even more favorable. This trend will develop more and more, app developers will therefore have to work to adapt themselves to natural interfaces.