Thursday, July 14th, 2011

moodMixer, for mp3 player and library

Music is an intensely social and emotional medium, yet the typical interface design for a digital music library (such as iTunes) is text-heavy, list-based, and closed to social interaction. moodMixer is a prototype visual/emotional/social interface for an mp3 player and personal music library, that dynamically leverages crowd-sourced, social data from The software acts on a user’s existing music library, compiling a list of songs and accessing a data set of user-generated tags for each song from, via that site’s API. For each song in the user’s library the set of tags is evaluated for keywords relating to emotion. Each song is sorted into one of 8 emotional categories: aggressive, chill, gloomy, melancholy, hyper, happy, romantic, and sexy. Each emotion is assigned a color code. In the interface, by clicking on color-coded blocks, the user simultaneously defines his or her mood (current or desired) and creates a novel playlist of randomly generated songs, reflecting his or her mood. The feedback is immediate and highly visual, and includes a clear temporal element: the color arrangement within the playlist indicates how the mood of the music will change over the length of the playlist. Within the player, the individual tags from the data set scroll across the screen, adding a social, almost conversational feel to the listening experience. moodMixer combines the popular random shuffle feature with mood categorization and social data, enabling users to make a more satisfying mix without the effort of handcrafting a playlist.

This project was independently conceptualized, designed, and coded in Java/Processing during an internship with the Creative Systems Group at Microsoft Research, Summer 2009. Thanks to Shane Williams and Tom Bartindale for their support and assistance with this project.

Saturday, June 18th, 2011


This project seeks to strip away the dominant, semantic aspects of a text and explores and expresses its purely formal qualities, the underlying skeleton of the text. textApart is a Processing application that visualizes the structure, rhythm, and phonetic patterns of a collection of words. TtextApart displays the selected text in a series of views, where the text is abstracted into shapes and patterns. Stacks of word-shapes and identify repeaters, uncommon word-shapes swell and common word-shapes shrink. By comparing text, we can discover the differences and similarities in what’s hidden under the message– in the mechanics of the text. In these examples, texts by Henry James and Brittany Spears are visualized and compared.

Tuesday, June 14th, 2011

The Semantic Thermometer

The Semantic Thermometer is a playful, visual way to display current local temperature data. The program takes a location and accesses up-to-the-minute weather information for that location, using Yahoo’s Weather API and a Where-On-Earth Id. The current temperature reading for that location is translated from a number to a corresponding descriptive word (for example 77 degrees Fahrenheit would be translated as “warm” and 24 degrees Fahrenheit would be “frigid”) from a set of words I defined. The program sends the word to the Flickr API, where it searches for and retrieves the latest user-generated photos tagged with that word. These photos are displayed in a grid on the screen, with a new photo added every few seconds to show the current local temperature in images. When the user rolls over an image, the descriptive word appears. The Semantic Thermometer invents surprising and baffling new metaphors, as it works in the gap between a specific physical experience and the imprecise, complex language we use to describe it.

Thursday, April 21st, 2011

All the Dairy Queens, Melting

A visualization of all the geographical locations of Dairy Queen Shops in the USA, displayed as drips of melted ice cream on a hot sidewalk. This program was written in Processing.

All the Dairy Queens, Melting from zannahlou on Vimeo.

All content © Copyright 2017 by Zannah Marsh.
Subscribe to RSS Feed – Posts or just Comments