Speech to text and Sherlock
#day10 of #100daysofcode
Today I explored how speech to text API works and sherlock. It was fun experimenting with them. I like exploring and checking out how things work. Sherlock is a great project on GitHub. We can use it to search username on various sites. You will find it great and could add it to your tool kit for tracking someone. And for fun just search your username and know how many sites have that username registered.
I used them to see the results. Sometimes looking at the results give us the motivation to build something new which could solve some other problem. I will explain to you the basic procedure to follow to get them running in your systems. I can assure you it is pretty easy. Let’s first look into speech to text.
We need to install the SpeechRecognition library of Python for it. It is simple to install just type pip install SpeechRecognition terminal. I wrote a very simple code to use it. There are two ways to use it. First, we could speak and get the text in real-time. Second, we can use recorded audio and convert it to text.
Let’s discuss the code.
First, we need to import the library(of course!!). I created two functions one if we want to use it for converting audio in real-time while we are speaking and another one for converting recorded audio. We need the internet for it to work. As it uses Google API to convert audio to text. It works very well and I liked the output. Though we are not training any model here. It is not that accurate and perfect but it is good for starting. For better results, we can learn more about it and can work on noisy input. It actually does not work with noisy audio. You can find the whole code here.
The next thing I explored is Sherlock. It is an open-source GitHub project which can help you find whether a username is present on a website or not. It extensively searches various sites and nicely outputs the results. It is very simple to use. You can check it out on GitHub here. Installing and using steps are well defined in the README file.
This is it for today. Keep learning and keep sharing.
Happy Learning!!!
