Notestream: Useful nodeJS Modules

My thesis project Notestream was built on top of nodeJS and Express. What has really sold me on nodeJS is the active community and the amount of modules available for use.

Here are a few modules I found useful during Notestream's development.

Shred

Shred is an HTTP client library. I used the Shred module for AJAX posts when I wanted to append more meta data, but didn't want to slow down the user from advancing to the next page.

For example, Notestream users save a Vimeo video to their video collection in order to mark it up with annotations. After a user submits the 'save video' form, Shred allows the server to gather additional meta-data from Vimeo after the AJAX post is made. It's all happening in the background.

JSON2csv

Another useful module is JSON2csv, and title pretty much says it all. Notestream users can download their notes in csv format thanks to JSON2csv. The module pings the Notestream API when a user chooses to download their notes, and formats the JSON accordingly.

Tock

Tock is Javascript countdown clock and timer. Why use this when JS already offers interval and timeout function? Because they're not very accurate. What's awesome about Tock is it self-corrects the time based on the system clock, so it won't lose track of the time.

Notestream Overview

I've been pretty slammed with end of the semester projects and work, but I at least wanted to mention my thesis Notestream. I plan on expanded on my process building Notestream in the coming weeks.

Summary

Notestream is a web-based annotation service geared towards collaborative mark-up of video.

My inspiration for Notestream is based on my love for watching online lectures. Naturally, there's usually a lot of information to glean from a lecture that typically leads to questions about material covered. Because the material is prerecorded you can't ask a question of the instructor on the spot, or start a conversion involving the class.

Notestream is built upon the idea that there is a community around a lecture. Students and instructors alike will want to append information that is touched on in a video. Perhaps an instructor left out some information in the video, or would like to give more resources for a topic touched on in the video.

That's where Notestream comes in. Annotations are made according to timecode.

Inspiration

While building Notestream, I constantly questioned who this service is for. I knew I would personally find this service useful, but would other people? As there is more of shift from in class lectures to online lectures, people will naturally want to break from the solitude of learning on their own, and use available resources to discuss the material being taught.

While there are timecode-oriented annotation services in the wild, I wanted to assemble my own flavor. Why? One, as a challenge for myself, but two, from what I've seen of the services offered, there's not a lot of emphasis on the comments themselves. They're usually relegated to the bottom of the page, or they sit in a static position as an aside.

A concept I am very drawn to is the Soundcloud waveform interface. Having messages animate on based on timecode, and indicating where in the audio files these messages are located really struck me as a concept to explore in relation to video.

Unfortunately the interaction doesn't work out so well for video. For instance, Youtube employs an optional annotation service inside the video itself. It feels cluttered. Also, given the nature of the annotations for lectures, which would typically be a longer note or sentence, the design doesn't map well to online lectures.

Notestream has a ticker area for annotations to fade-in and stay for six seconds, then disappear. I experimented with different font sizes and animations, and the old addage "less is more" was best suited here. In fact, the design of Notestream is all very spartan - flat UI, lots of whitespace, and inconspicuous typefaces.

Building it

From the get-go I was very focused on building Notestream from the ground-up instead of top-down. Most of my attention was focused on mapping the database and server to how I envisioned Notestream to work, while the front-end would naturally materialize out of that back-end infrastructure. Notestream is built on NodeJS/Express and MongoDB.

You can demo Notestream here. If you have any questions or comments, feel free to message me.

The code is available on Github.

Python Haiku Generator

In the same vain as my poem generator, I have coded a haiku generator in Python. Initially I wanted to write a haiku generator before resorting to a poem generator, but I could not find a source for the number of syllables for a dictionary of words.

Well, that problem is solved — Carnagie Mellon offers a pronunciation dictionary, for their speech-to-text engine, Sphinx. The dictionary is open-source, so I am using it as a source for words and syllables for the haiku generator.

Haikus are traditionally three lines, with a 5-7-5 split, or five syllables for the first line, seven syllables for the second, and again five syllables for the final line. If your middle school days of English class are beyond your recollection, it looks something like this:

An old silent pond...

A frog jumps into the pond,

splash! Silence again.

The CMU dictionary is simply a text file with each word split into the following format:

AGENCY  EY1 JH AH0 N S IY0

The line starts with the word, then two whitespaces and the pronunciation with numbers indicating the syllable breaks.

I wrote a function to break these lines down into a word and a syllable count, which is then stored in a Python dictionary. The dictionary is set up with the syllable count as the key, and the list of words with associated syllable count as the values.

The final part the code then builds lines depending on the amount of syllables desired, which is then constructed in a final function in a haiku format. Here is a sample of outputs:

MUSTAFA WILSON'S

WONDERFULNESS JAWED BARBY

WORLDERS BAS-RELIEF

---

BATTERERS FOOTLIGHTS

STRIKE KONARSKI HARDYMON

CHOO STRANDS SOLIDLY

---

SPATH RASH SPIKE MUCUS

UNDERLINING SCREWDRIVERS

STOUT SEALED VOS HANZLIK

---

Check out the code here.

Python Poem Generator

Our Reading and Writing Electronic Text Midterm projects consists of two steps:

• Devise a new poetic form.
• Create a computer program that generates texts that conform to new poetic form you devised.

Initially I wanted to create a haiku generator. Unfortunately there are not a lot of online resources dedicated to breaking english words down by syllable. Instead, I settled on a poem generator.

The python script scrapes a random word generator at Vocubula.com, where it gets the word and the word's part of speech. From there I organize the words according to parts of speech inside a dictionary, where the part of speech is the key, and the values are lists filled with the words.

I also scraped a list of prepositions to insert into the poem structure.

The poem structure itself is four lines, and each line is a simple sentence structure.

The poem generator has created works such as:

cacography popple incunabulum through the exuviae
nympholepsy versus ensorcell skeuomorph
inhere subfusc triumphalism
cosmography disabuse by means of gourmand

Or:

detritus perambulate bacronym against the caducity
Weltschmerz in front of enucleate suborner
notional soi-disant succedaneum
zoophyte embay modulo gourmandise

And finally:

quatopygia straiten menology neath the anonym
incubus left of transude quiddity
perambulate chthonic juvenilia
maenad ameliorate above zenana

The output reads like a Harry Potter spell. While it's not very impressive, perhaps there are more variations in the line structure to investigate.

The code is available here: Github.