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Survey of relevant background material
Concepts and Inspiration
There are many underlying concepts that run beneath this project, each of them is as important as the next. When the group was given back the suggested ideas at the start of the semester, we were presented with two distinct directions for development. One path lead towards conversation monitoring, sound manipulation, speech recognition and sound analysis – While the other, lead towards life-as-art, responsive seating, reflection and sound feedback. It was our job to join these two distinct areas together into a cohesive new project.
Eventually we came to the idea which is being presented in this report, an “oracle” that gives advice, based on a certain keyword related questions. The base concept that we are using as a guide would be an “oracle”. Oracles traditionally were those who could predict the future. They would often offer advice on a certain situation and give guidance and council for those who were searching for it. Of course, this is the ancient traditional oracle, if you were to examine the equivalent today, you'd be reading horoscopes, calling psychic hot lines, or getting a tarot card reading in a shopping centre mall. This is the foundation for the physical aspect of our project. The technical and aesthetic aspects were inspired by a combination of elements including each group members' specialities and interests.
Related Projects
“The Turing Test” and Artificial Intelligence
While this test is not specifically a related “project” the concepts behind this test are closely linked to the ideals behind our project. The Turing Test ( Designed by Professor Alan Turing ), is a test to see if a computer can mimic human conversation. In short, the test requires that a human judge has two conversations, one with another human, and the other with a computer. If the judge can not tell which is the machine, and which is the human then the machine passes the test. The Turing Test is a test of artificial intelligence, and in a way, if a machine can pass the Turing test, then that computer would almost appear to be a human being itself. With our project attempting to simulate the presence of another person, some form of AI, or AI behaviour would help to hide the machine behind the exhibit.
Talk2Me, at ReActive exhibition – Ann Morrison
A related exhibit which a previous studio lecturer ( Ann Morrison ) put together at “The Block” ( QUT, Kelvin Grove ) Involved a user speaking into a microphone and “talking” through a computer. Although the exhibit only had a small amount of text to speech conversion, there was still enough interactivity there to show the possibility of future implementations. A brief email from Ann mentioned that she used the inbuilt mac osx speech recognition engine to get the user input
http://www.itee.uq.edu.au/~morrison/ for more information visit http://anmore.com.au/talk2me/talk.php
AuraLamp
AuraLamp is an experiment in “contextual” Speech Recognition. Ie, and object that knows when you're speaking to it. Currently with speech recognition software, it always assumes you are talking to it ( usually controlled by a “stop listening”, “start listening” command ). This project tracks the Eye Contact of the participants, and only responds when someone is looking directly at the lamp itself. Our project considered a similar problem of knowing when to listen, and when to ignore. Although the eye contact technique wont work in our chosen environment ( instead, we've gone with the pressure sensor , or similar system ), the concepts behind this project aided us in our realisation.
http://ubicomp.org/ubicomp2003/program.html?show=demos Title - “AuraLamp: Contextual Speech Recognition in an Eye Contact Sensing Light Appliance”
Technologies
The main technologies used in this project will be speech recognition, as well as the ability to analyse, and store recorded messages depending on a category or keyword.
Speech Recognition is an extremely complicated and ever-changing technology. There are many strategies for implementing it, as well as many algorithms and techniques for acquiring the speech data and making it available for analysing. Speech Recognition is the process of converting a speech signal to a sequence of words. For example, someone says the words “I like studio” into a microphone, the computer recognises the sounds produced and the words they make, and can reconstitute text or commands based on that information. Modern day speech recognition systems use the “Noisy Channel Formulation”, in which the system will search for the most likely word given an incoming signal.
Our project will rely heavily on speech recognition as the users will be speaking to the exhibit directly. It must either be able to store sound data as a recorded file, or analyse the incoming data, and store that information as text.
Further technological requirements would include a database system for storing information, as well as a way to provide possible statistics for users as they interact with the system.
A variety of options are available as to a technological source for the majority of the programming. Currently the best option seems to use the program “Processing”, which allows for dynamic recording of speech, as well as possible modification and analysis. Other options include using external programs for individual elements with a core module tying them all together.
Sources
http://www.turing.org.uk/turing/
http://www.turing.org.uk/turing/scrapbook/test.html
http://processing.org/
http://www.ling.lu.se/research/speechtutorial/tutorial.html