Entering a new domain! Making specifically this bookmarklet (delete bookmarklet) was Simon’s idea. He learned to make bookmarklets today during Daniel Shiffman’s live session on basic bookmarklets and Chrome extensions. The video below is basically only watchable in the beginning and the end (Simon filmed himself debugging in the middle, feel free to skip that 🙂
Simon is now working on a Chrome extension that would do the same as the bookmarklet he made – delete words. He says that a Chrome extension is more sophisticated and involves more code. He is currently halfway through. the picture below shows Simon and his giant Chrome extension button:
Screenshot of the browser:
Excerpt from Simon’s conversation with his friend programmers in Slack today:
Simon has just finished working on his first library, a #speechlibrary Speechjs. You can find Simon’s library on GitHub: https://github.com/simon-tiger/speechjs
Simon also added a reference page at: https://github.com/simon-tiger/speechjs/wiki/Reference
You can use this library for any project that uses #speechrecognition and/or speech synthesis. Simon has put it under the MIT (permissive) license, to make sure everyone can use it for free, he emphasized.
While writing the library, Simon also recycled various code he found online, but essentially this library is his own code. He calls the library “just a layer on top of the web speech API” (that means you’re limited to what your browser supports).
Following the exciting text-to-speech and speech-to-text projects yesterday, this morning Simon made a basic speech-to-text-to-speech demo, which means that the computer can now repeat (parrot) everything Simon says.
Simon relied on what he learned during Daniel Shiffman’s two latest live streams on the Coding Train channel in building these projects.
This is one of those wow projects, so much fun! Simon built his Text-to-Speech and Speech-to-Text demos following Daniel Shiffman’s recent live streams on working with the p5.Speech library and added some extra style features. This basically means that you can type anything on your computer and hear it say what you’ve typed (in any voice or language!) or, in what Simon said was an easier project, yell something to your computer (I love you!) and watch it type it out for you. The next step will be combining the two and including that code into a chat bot code.
You can play with Simon’s Text-to-Speech demo on GitHub at:
Basic text to speech example: https://simon-tiger.github.io/p5_speech/01_text2speech/
Example using different voices: https://simon-tiger.github.io/p5_speech/02_voices/
Basic speech to text example: https://simon-tiger.github.io/p5_speech/03_speech2text/
Code/ repo: https://github.com/simon-tiger/p5_speech
Simon has continued with server side programming and made a spellcheck API! Here is the link, you can play with it yourself by adding new words to the corpus (dictionary):
Here is how the API works:
And the making of, step by step:
The project is partially based on what Simon learned from Daniel Shiffman’s tutorials about creating web servers and the materials available online in Daniel Shiffman’s Programming A to Z course (analyzing and generating text-based data) and is partially Simon’s own code.
Simon has made his version of Daniel Shiffman’s Wikipedia Crawler, graphing the relatedness between Wikipedia articles.
Play with it yourself online at: https://simon-tiger.github.io/wikipedia-crawler/wikipedia/
How it Works
Enter a query (e. g. apple) and either hit Enter or press the button “Query the API”. If an article called “Apple” exists, a circle will pop up with th word “Apple” in it. If an article called “Apple” doesn’t exist, a circle with something alse will pop up. Click the circle (or article) to reveal its related articles. As you might expect, you can click any of those articles to reveal its related articles.
The inspiration comes from Daniel Shiffman and its Coding Train. Link to Daniel’s version here.
A milestone in server side programming here, as Simon has built a text generating machine that posts to Simon’s Twitter account! Essentially, it’s website where anyone can enter his own text for the machine to make a “poem” from using an acrostic algorithm; the machine simultaneously posts that “poem” to Simon’s Twitter.
This project falls under the topic of building an interface for Twitter. The original inspiration came from Daniel Shiffman. Simon writes:
You can try my Acrostic machine at http://acrostic-tweeter.herokuapp.com/ and it tweets to my account at https://twitter.com/simontigerh/
In this scenraio, I’m feeding in some text and a word. I’m clicking a button, to tweet the acrostic. I used node to create the server. I later put that server on heroku.
I’m also using a couple of packages:
– express – to host my interface
– socket.io – for the server and the client to talk to eachother
– twit – to tweet the acrostic
In the previous video, I got everything working, except that after I try to use heroku (by typing `heroku login` in git bash), What appeared was:
“`bash: heroku: command not found.
Later we solved this issue by using command prompt:
Simon got positive feedback on his project from Daniel Shiffman, who asked Simon to give some explanation about what the machine on the webpage and also to give a link to Simon’s Twitter:
Last Friday Daniel Shiffman was finally back with his weekly livestreams! Simon was delirious with joy that he could be part of the team again and weeping and panicking every time Daniel experienced technical difficulties. During the days that followed, Simon made his own two versions of the coding challenge Daniel presented in the livestream and shared those with his colleagues on GitHub and the Slack channel: “I made *two* versions of the acrostic coding challenge. Link to a github repo: https://github.com/simon-tiger/acrostics (Links to both of the versions in the README).
The coding challenge was part of Daniel Shiffman’s Programming A to Ze course at NYU (a course focusing on analysis and generation of text-based data) and was about creating an Acrostic machine – an algorithm that would use a source text to create a “poem”. Every word in the poem would begin with the consecutive letter from a word one enters.
One version that Simon created uses an API as the source text:
In the second version, the user can type the source text (like in the screenshot below), use a text sample or drag a source text file into a special dropbox:
Screenshot of the second version (with drag and drop):
Simon making his versions of the Acrostic machine: