Digital Lanugage Arts

I made a good amount of progress on my final project. I scraped all the articles from the Brown Daily Herald and used a sentiment analysis classification tool to assign each of the articles a score (https://github.com/aanshshah/dla_final_project). Next, I started the scene that I am going to be using for the project in a-frame. I created a 'wormhole' and the article text is read to the user via a text to speech API while the user is brought further into the 'wormhole'. The user is stuck in the wormhole during the entire experience as any interaction with the webpage repositions them within the wormhole. The next tasks I need to complete are adding articles from 2009-present to the experience, changing the background color, changing the wormhole color, and adding more interactions to the web-experience. The current version iteration of my final project can be viewed here:  http://aanshshah.com/dla_final_project/

For this week's experiment, I decided to do a homophonic translation of a poem by Pablo Neruda. To find this poem, I googled homophonic translation. I wanted to see how close I was at a "good" translation and so I found the same poem translated into English from Spanish. For some additional context, I am familiar with the Spanish language, but it's been a couple of years since I have practiced or communicated in Spanish. Original Poem: Juventud by Pablo Neruda Un perfume como una ficida espada de ciruelas en un camino, los besos del azficar en los dientes, las gotas vitales resbalando en los dedos, la dulce pulpa er6tica, las eras, los pajares, los incitantes sitios secretos de las casas anchas, los colchones dormidos en el pasado,  el agrio valle verde mirado desde arriba,  desde el vidrio escondido: toda la adolescencia mojfindose y ardiendo como una lÿmpara derribada en la lluvia. My homophonic translation: Youth  by Pablo Nemda

Project Title: Changing Attitude Summary: In this project, I will look at how the sentiment in articles published in The Brown Daily Herald has changed over time. I will scrape all the articles from the Opinions Section (columns, letters to the editors, editorial, and Op-Eds) and analyze the sentiment. I will then find “the average sentiment” from 2015-present and choose representative articles for each of those years. Then, in a 3D experience, the audience will hear a computer voice read an article from each year. Instead of displaying the text to the user, the user will only see the color around them changing as the sentiment of the article changes. The audience will be taken through the change in sentiment over the years via the articles. Details: Concept: I think it’ll be interesting to explore how the experience varies from reading a text-based article. In this experience, because you do not see the words and are influenced by the changing colors, I am curious to see how it

This week's reading draws an interesting parallel between machine translation and natural language. At one point, the author argues that there is an important difference between programming languages and natural language, arguing that we can never truly have perfect machine translation. I thought that this was an interesting parallel because language is grounded in rules and programming languages consist of a series of rules. Thus, we ought to be able to reconstruct something that makes up a series of rules using other rules. The author treats machine translation as a black-box, whereas we know exactly how these models are being generated. The program is being fed a corpus that contains a body of text and the "right" translation. Hence, we have complete control over how texts are being translated; the only necessary component to change is the corpus to obtain a better translation. Knowing this, we are able to produce very literal translations. The author uses the concept

A collabortation with Abraar, Elizabeth and Rhythm: https://drive.google.com/file/d/1ELJqEijlnQF_7jXDJaFv5l53-aqClEG6/view