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Wednesday, September 19, 2007

Human Identification Algorithm

Are you human? (Sorry, We Have to Ask). Can’t read the text? Listen to it.
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You have seen it time and time again. That required step when you submit stories these days for human identification. It composed with letters that are salted with noise and artifacts to defer a bot's attempt to fill out the form and thus spam.

It was a smart idea, but algorithms catch up and soon they don’t work quite as well anymore. So the level has of difficulty for OCR comprehension increased bit by bit everyday. It has become so complex these days that even I cannot identify what characters they are supposed to be.

Perhaps because of the number of complaints received, now we also have the audio version of the same thing. What are they going to do when the audio recognition algorithm got better?

In my opinion, this human identification process simply does not work. Algorithms will get smarter everyday for visual or audio algorithms. A better way is to ask logic questions. For example, ask people to verbally describe the difference between a nerd and a geek. Ask them why they they are reading your blog.

Opinions are largely based on logic, but it is also largely based on creativity, and creativity is something that cannot easily be programmed yet—until the natural language algorithm catch up on it. Another difficult thing that comes natural to us but fairly difficult to do for a machine is comprehension.

I have tested this behavior with a survey which ask the question: Name the odd-man-out among the following: AOL / Google / MSN / Yahoo and state the reason supporting your answer. I get very interesting answers. They are all very inspiring and as such I know that they are not machines.

Being able to go through those answers and pick out the human responses are also most definitely a task that ought to be done by a human. I do not think that there is a computer program that can decipher how creative something is yet. However, I have fears that there are projects underway that is attempting to understand creativity using brute force.

A couple of weeks ago, I went to Google Answers, and I discovered that they are no longer accepting new questions. This was a site where users submit questions and get answers responded by other users. The snippets are very interesting and no doubt allow Google to index more interesting data that is not readily available on the Web. Having the ability to train an algorithm to act like human is a very ambitious activity, but it appears that the algorithm training has paid off.

I visited Google Translate and Google Language Tools recently and I am very impressed with their English to Chinese translation capability.

Unlike English, Chinese uses a defined set of characters. Where Latin languages generally create new meanings by the use of new words, the number of Chinese characters do not change. New meanings are created through the combination of the order of these characters. As such, while Chinese children are rarely able to read newspapers until they are graduating from primary school, there will be no more new words to learn after that. It's all pattern recognition after that part. It's a bit like iconography systems, where new meanings are created out of a predefined set of modifiers.

Despite the language's complexity, I witnessed that the Google Translator is able to handle English to Chinese text relatively easily, which is light years ahead of the translation tools I have used before, and it definitely makes me wonder what else Google Research is brewing inside their labs these days.

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Copyright 2007 See-ming Lee 李思明 SML / SML Pro Blog / SML Universe. All rights reserved.

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