How to Build an AI Personal Assistant from Scratch

Lately, there has been a buzz around voice assistants that have been trending for business and personal use. For instance, virtual assistants such as Siri, Alexa, Bixby, Google Assistant, etc. have invaded our mobile phones, making our daily life more comfortable. 

How many times have you used an AI personal assistant just to send email for you? Many times, right? As you can see, the application of machine learning to your daily life activities is endless. Whether you use the AI personal assistant for making appointments, setting reminders, finding the shortest route to work, or searching something online, we can see how deeply integrated AI is into the tech that we use. 

Even though each artificial intelligence assistant is different due to its features, all of them function on the same principle. They receive external data, including voice, movement, light, visually defined markers, GPS readings, etc. through the hardware’s sensors. From there, the open source data is processed, and it functions accordingly. 

Not too long ago, building an AI intelligent personal assistant was a thing that only a small section of developers could do. However, today it’s a realistic objective that novice programmers can work on. It’s all about following the simple steps, sometimes, and dedicated software. 

In this article, we’ll discuss the operating principles of the AI assistant, go through the most popular APIs for AIA development, choose a programming language and test out your assistant for providing the best user experience. Therefore, you’ll get an idea about how to build an AI personal assistant. 

How AI Personal Assistants Work?

Before you go on and build artificial assistants, you have to go through the basics of how they work. AI personal assistants can make their own decisions based on incoming data. Behind the individual choices, there is a set of tools that process received data. Due to neural networks, abilities such as natural language processing, voice recognition, and voice commands are easily integrated. The systems are, in fact, an imitation of the human brain and help the personal assistant in data analysis, recognition, and classification. 

Just for the AI personal assistant to process information, you don’t have to do a manual input, but instead, use an API (Application Programming Interface) software for that purpose. The API software provides aid to the apps and face recognition, documents, speech, and other external factors. Since there are many APIs on the market, we’ll go through the most popular ones from which you can choose to build your very own AI personal assistant. 

What API Should You Choose?

If you have questions concerning the API keys, or anything revolving around API, you need to have a detailed look into the features that each of the API platforms offers. 

Wit.ai

This speech API has tools for converting voice commands into text, mainly dedicated to generating users’ answers and analyzing them. Wit.ai is based on two notions, the first one being the entities and the second one based on roles. Therefore, the platform will automatically outline the main subject of every request. For instance, in the question “Where do kangaroos live?” the main item is “kangaroos.” 

Besides, the name of the subject can refer to different contexts, and the list of possible actions of the software will extend once the request is recognized. The advanced development functionality of Wit.ai includes a “history” option enabling simple conversations based on predefined algorithms. This platform is available on iOS, Raspberry Pi, Android, Node.js, Ruby, C, Python, Rust, and Windows Phone developers.

Amazon AI

Amazon AI recognizes live speech, text translation into text data, automated deep machine learning based on the operation of artificial neural networks, search and identification of visual objects, etc. Because of all these features, this platform is ideal for custom development implementation and lightweight applications carrying minimal loads.

IBM Watson

The computer system is developed in C++, Java, and Prolog, getting information from outside and translating it into machine code. The idea behind IBM Watson is to have a multitasking, high-performance system.

The algorithms in this system are made by organizing them for investigating multiple parameters, rather than analyzing key phrases coming from the external environment.

IBM Watson is an excellent idea for creating an AI-driven deep learning marketing solution because of the following features: processing decision automation, live speech, powerful search engines, and machine learning.

Google AIY

Google AIY is the ideal platform for building your own smart speaker. It’s an open source tool that enables components, code, and code segments to be made available on the internet.

This way you can easily find appropriate modules for your own AI personal assistant. The data are organized in blocks of code, which you create according to your needs.

Api.ai

The data that Api.ai uses is based on the experience of human interaction since Api.ai is a section of the Google platform. Api.ai is different from the other software because of the domains. The domains are data and knowledge used by agents, making this platform all about details.

The comprehensive information within the software provides vast answers to educational questions. Just because of these features, Api.ai is the most commonly used platform by developers. It can be used by iOS, Android, Node.js, Apple Watch, C++, Cordova, Phyton, Xamarin, and Unity. 

What Programming Language Are You Going to Use?

Some of the trendiest programming languages that are used for creating AI-based apps are: Java, Prolog, Lisp, and Python. The most commonly used of them all is Python, being known for its simplicity and flexibility, for over 20 years since its creation. 

If you choose Python for building your AI personal assistant, the first steps would require you to install the following packages into your system by using the pip command. 

• Speech recognition
• Pyttsx3
• Ecapture
• Wikipedia
• Os
• Time
• Datetime
• Subprocess
• Web browser
• Request
• Json
• Wolfram alpha

In addition, you should import the libraries from below:

import speech_recognition as sr
import pyttsx3
import datetime
import wikipedia
import webbrowser
import os
import time
import subprocess
from ecapture import ecapture as ec
import wolframalpha
import json
import requests

Once you install the packages and import the libraries, you will be able to continue further on with the setting up of the search engine, initiating a function to greet the user, setting up a command function for the AI assistant and proceed with the main function.

Do the Testing on the Personal Assistant App

Even though a personal assistant app can be created, its development shouldn’t be underestimated. It’s because this type of work requires finances and a significant amount of time and dedication. Maybe that’s the reason why companies are choosing some of the ready made platforms as a starting point, instead doing it from scratch. Once they create a unique product, there comes the phase when the app has to be tested. So, here’s what the testing includes: 

• Analysing of the user interface
• Analysing the quality and speed
• Memorization of the individual user interactions (route optimization, time management, topics of general education, informal conversations with assistants, etc.)

Conclusion

For developing a personal assistant, the main features that need to be taken into consideration are: its programming language, the type and quality of data used, and also the apps’ features. These features can be divided into three categories: performance improvements, user experience improvements, and security improvements.

If you decide to create an internal personal assistant for your company, this no longer is rocket science, but can actually be done. There are several API platforms that offer you support in doing so, while you get to add features that will be tailored to your needs. Sometimes all you have to do is try and see how far can you go in building an AI personal assistant app.