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The big idea that many people hope to attain through their businesses is the ability to create their own virtual assistant and delegate tasks in order to free up time to focus on the things they enjoy. What if you could build your own Siri-like virtual assistant, program it with all the knowledge you have, and use it to streamline your business? Now, what if I told you that you could do that within an hour? You can! All you need is an Internet connection and your favorite browser. And by the end of this post, you’ll be well on your way to automating some of your workflow tasks.
This guide will walk you through creating your own personal assistant that works just like Siri. By following these simple steps, you can create something powerful enough to hold productive and engaging conversations with colleagues and friends. What do you get when you combine artificial intelligence and voice recognition? An awesome virtual assistant! This is something every entrepreneur should have. This post is broken into four parts: choosing your tools, writing your bot’s code, training it, and deploying it on Google Cloud. By following along step-by-step, you’ll be able to stand up your very own virtual assistant using AI technology in no time!
What Is Deep Learning?
Deep learning is based on deep neural networks, which are hierarchical (multi-layered) machine learning systems that can model complex relationships. They’re particularly useful for tasks such as image recognition, speech recognition, and natural language processing. Tasks that we consider simple for humans – recognizing words or sounds, performing complex math operations in our heads – aren’t easy at all for computers. Deep learning aims to solve these kinds of problems using neural nets.
- Based on deep neural networks.
- Useful for image recognition.
- Useful for speech recognition.
- Useful for natural language processing.
TensorFlow is Google’s open-source implementation of machine learning software. It’s designed for easy and fast training of neural networks and has quickly become one of the leading platforms for both research and production in ML. Developers can install TensorFlow with either pip (for Python) or Homebrew (for macOS). If you’re new to ML, start here before moving on to more sophisticated frameworks like PyTorch or Caffe2. For an excellent collection of useful tutorials, check out DataCamp’s Introduction to Machine Learning course or Udacity’s Deep Learning Nanodegree.
- Easy and fast training of neural networks.
- Leading platforms for research and production in machine learning.
Load Data Into The Model
According to Wikipedia, Siri uses an application programming interface that allows some of its functions to be accessed programmatically by programs and scripts written in various programming languages. Third-party developers can write applications that plug into Siri’s functionality. With a great deal of market interest, you might consider providing a plugin or extension platform for those who wish their product or service could benefit from talking directly with users via AI. In order to do so, data must be collected and loaded into your Model. For example, what are users saying on Twitter? What are they saying on Facebook? What are they saying on Google+?
- Allows some functions to be accessed programmatically by programs and script.
- Can write applications that plug into Siri’s functionality.
Train The Model
You will use TensorFlow’s built-in natural language processing and speech recognition models to translate user input into actions. All of these models can be trained using Python code, meaning you don’t need specialized expertise in machine learning or deep learning. The hardest part of using TensorFlow for NLP is properly creating your data set (see Google’s guide here), but once you have it, training models with TensorFlow are relatively straightforward. And if you want a visual overview of what all these words mean, check out Google’s project on visualizing NLP here.
- Translate user input into actions.
- Trained using python code.
- Creating your data set.
At its core, any virtual assistant is just a computer program that’s designed to automate tasks—tasks you’d usually complete on your own. You can think of it as installing applications on your phone: You can choose which apps you want and how you want them to operate. The only difference is that with voice software, we aren’t using our fingers; we’re using our voices. There are two basic types of voice software: Speech-to-text (STT) and speech recognition (SR). With STT, you’ll need some sort of keyboard or user interface built into your technology; with SR, no such device is necessary. Let’s look at both options for creating your own virtual assistant and deciding which one works best for your purposes.
- It is designed to automate tasks which complete on your own.
- You can choose which apps you want and how you want them to operate.
- You will need some sort od keyboard or user interface built into your technology.
Try It Out!
First, head over to Github and grab Siri-Speak. This is a simple Node script that will analyze what you say and outputs it as text. It’s not designed for mass consumption, but its underlying code should show you how quickly your personal virtual assistant (VA) can be created. You could even take out any parts of the code that personalize it for your own name or add them back in later. All of these little variables are customizable, so tweak them to your liking once you’ve got things up and running. From there, just plug into IFTTT: Incoming text messages—like those from an iPhone—can trigger IFTTT applets (basically like macros), which work with other connected services like Google Drive or WordPress. If you are interested to learn new coding skills, the Entri app will help you to acquire it very easily. Entri app is following a structural study plan so that the students can learn very easily. If you don’t have a coding background, it won’t be any problem. You can download Entri app from the google play store and enroll in your favorite course.