Top 3 Efficient Approaches
Artificial intelligence became part and parcel of some software. Today, it can analyze the data, recognize the speech, make search queries, and so on. The connection between AI and everyday life grows stronger every day.
A lot of entrepreneurs and software development companies focus their efforts on creating AI assistants. Soon, the presence of the voice interface will be taken for granted. In this post, we will go through the development nuances of virtual assistants. Let’s go!
There are three ways to make virtual assistants understand the speech and engage conversation.
- Ready-made integration. This method requires you to integrate existing voice recognition solutions into your app with the help of APIs.
- Independent solutions. If you want more flexibility, you should try independent voice assistant APIs. They let you build your own assistant with features provided by those APIs.
- Voice assistant from scratch. The third method is the most complicated and expensive. You can develop a voice assistant that will meet all your requirements and integrate it into your application.
To shed some light on all the benefits and disadvantages you will face, let’s take a closer look at each approach.
According to the recent research by Microsoft Siri, Google Now, and Cortana are the most well-known of all the mobile assistants. So, now we will focus on these three solutions.
Since Siri was first introduced for development purposes in 2016, it underwent significant changes. For now, Siri can be used in fields that concern:
- To-do lists and reminders
- Car management
- Taxi and delivery services
- Smart home app development
- Payment systems
- Workout applications
- Sending text messages and making calls
Apple developed SiriKit to enhance the convenience of the development process. This library consists of two frameworks. One of them is responsible for performing the action, and another one triggers the visual representation when the task is done.
Every app type from the list has to deal with a certain amount of tasks, which are called intents. This term is similar to the word intention and refers to the user behavior pattern.
In SiriKit, intents have predefined properties that describe the task they belong to. As an example, if a user wants to start a workout, properties will describe the type of exercise and the training length. After receiving the request, the system completes the intent object with specified data and sends it to the app extension. The final part processes the data and delivers the correct result.
Below you can review the scheme of intents processing:
Google Now and voice actions
Google has always been more tolerant to developers compared to Apple. Approvement period in the Apple App Store is much longer than in the Google Play. On top of that, the App Store has strict requirements concerning the app design.
When it comes to the voice assistant, the story remains the same. Google allows you to integrate an assistant in any app you build by using the Google Assistant SDK.
Try not to confuse Google Now with loads of commands. Remember that this is not only a machine but also a creature that can learn, analyze, and conclude based on your queries. If it sounds a little bit complicated, don’t worry. Google has very detailed documentation that will guide you throughout the development stages.
Microsoft’s voice assistant is available on smartphones and desktops. With Cortana, you can use voice control without directly calling an assistant. Cortana Dev Center provides developers with a full guide on how to make a request to a specific app. There are three ways to integrate the app name to a request:
- Prefixal. In this case, the app name stands in front of a voice request. For example, “Uber, get me a ride!”
- Infixal. Here, the app name is right in the middle of a voice request. For example, “Get me a Uber Eats food delivery!”
- Suffixal. The last one, where the name is placed at the end of a command. For example: “Get me a ride, Uber!”
With Cortana, you can activate the background or foreground app by voice requests. The first type is used for simple apps that don’t need additional instructions, like “What’s the time now?” Another type is for the apps that require complicated requests such as “Send the Greetings message to Emily”. Here, you specify the type of message and receiver.
Previous technologies are not the only solution for implementing voice assistant in your app. There is plenty of tools for AI fans. For your convenience, we have made a list of the most significant ones.
Jasper is the tool for developers that are used to rely on themselves rather than on external support. It’s a great software for Raspberry PI users because it executes on its model B.
Jasper is coded on Python. It can listen with the help of the active module, and learn with the passive. It is always on, so it can fulfill your requests at any moment. While studying habits without attracting your attention, it will give you precise information when needed.
Dialogflow can handle a lot of tasks, and one of them is the development of a personal assistant. It recognizes the voice and converts it into text for executing the tasks. As well as Jasper, this service can also analyze the data and draw conclusions.
Dialogflow has both free and paid subscriptions. The paid version allows you to work in a private cloud. So, if privacy is one of your concerns, that’s your choice.
Dialogflow has a number of APIs for different platforms and programming languages, including Android, iOS, Cordova, Python, C#, Unity, Node.js, and so on.
This service has something in common with Dialogflow. If you use this service, you’ll have to deal with two things — intents and entities. Here, intents are the actions that users want to perform., e.g., show the forecast. Entities are the properties of intents that make the requests clearer, e.g., time and place of a user.
The best thing is you don’t have to create the intents by yourself. Wit.ai has a prebuilt list of intents, so the only thing you have to do is a choice. Moreover, Wit.ai is completely free for public and private usage. Nevertheless, you still have to follow the rules and policies of Wit.ai while building a personal assistant.
If none of the above methods match your ideas, and you decided to develop a custom solution, make sure that you are qualified enough and have a decent amount of resources. Now, let’s get through some mandatory technologies for building a voice assistant.
Voice/speech to text conversion
The primary technology for your personal assistant. The user experience mostly depends on the recognition of the requests. The voice may transmit in the form of a file or a stream. The most well-known APIs are Google Speech-To-Text and Microsoft Cognitive Services.
Text to speech
The exact opposite process that converts text or images to a human speech. This feature may be used when a user wants to hear a pronunciation of an unknown word or to listen to the news read by an assistant.
Tagging and decision making
This feature serves for interpreting the request for the assistant. For instance, if the user asks: “What do I watch today?” assistant should tag the best relevant movies and suggest some based on your interests and recent search queries. AlchemyAPI may come in handy to overcome this challenge.
With this technology, your app will be able to isolate your voice from the environment noise. If you care about the user experience, you should definitely have this feature under the hood.
This option is an excellent addition to your assistant’s security. When it’s able to detect the speaker, the personal assistant won’t respond to third-person requests. Besides security, it also will avoid situations that occurred to Siri and Alexa when they turned off the climatization because of the appropriate command coming from a TV.
This functionality allows the client side of the app to compress the size of the speech data and send it to the server. This provides optimization on both server and user devices. One of the common compression standards is G.711.
Voice interface is a reply that the user can hear and see after making a request. For this part, you’ll have to find the voice, adjust the rate of speech, the manner of speaking, and so on. As for the visual side, you’ll have to decide what user is going to see on his screen. Surely, it is more of a brand image feature. That’s why you can skip this part for the first time.
Mind that you can process voice and text on a server as well as within the device. Below, you see the scheme that involves the server resources.
As we can see, each method has its benefits and weaknesses. Siri, Google Assistant, Cortana are the most popular and well known among users. Eventually, users would rather prefer something familiar over a dark horse. However, ready-made solutions often have limitations and don’t fulfill your expectations completely. Besides, they are strongly bound to specific companies and their platforms. These downsides lead to the development of inflexible software.
Standalone services simplify the process of integration. They have detailed documentation that will help to enable voice recognition in your app. Still, this approach doesn’t allow us to realize the full potential of your idea. Limitations of pre-written software take away the freedom of making vital changes in the assistant.
The only way to carry out a personal concept is developing a voice assistant from scratch. This method doesn’t restrict the flight of imagination, so you are free to create the software as you see it. Unfortunately, this approach is the most time and money consuming. While standalone services deliver ready-to-use basic features, independent development obliges you to build them from scratch. But it will definitely be worth the efforts.
Whatever approach you choose, the main thing to remember is to hire a dedicated team of professionals that will build your app in the shortest terms.
Vitaly Kuprenko is a technical writer at Cleveroad. It’s a web and mobile app development company in Ukraine. He enjoys telling about tech innovations and digital ways to boost businesses.