Julian Brown

Read More

As AI becomes an increasingly normal part of our every day life, we have come to rely on it increasingly. A growing area of activity is in speech recognition. Historically computers have always had some difficulty understanding the nuances inherent in human speech. Quite unfortunate considering human speech is such a fundamental aspect of our humanity, that one would suppose it to be crucial if we were to get anywhere meaningful with AI.

However advances in computational power compounded with developments in networked technologies have enabled computers to “learn”. This machine-learning has greatly accelerated the progress of demanding tasks such as speech recognition. Now it is commonplace for this technology to be found in most common everyday consumer products such as iPhone Siri or OK! Google etc.

Bable uses YouTube's build in experimental algorithm to provide automatic translations. The translations are frequently wrong. However in lieu of the correct translation, the audience is thrust into a position of interpolating a meaning nonetheless often to comic effect due to the absurd nature of non-sensical co-minging of wildly disparate concepts. Bable explores the mechanisms that govern our ability to determine meaning in the presence of non-sense and challenges our understanding of the role of the “passive” audience in determining successful outcomes of communication.