MetaTempoMorphosis

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The word “MetaTempoMorphosis” describes a transformation (morphosis) of our understanding of tempo through a meta-level analysis.

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This art project explores the modern human experience of accelerated time and life processes. At its core is an experiment with Beethoven's Fifth Symphony – Google's most searched Beethoven composition – compressed to play in just one minute. When accelerated to this extreme tempo, the symphony transforms remarkably into sound patterns that closely resemble birdsong, with its rapid trills and melodic fragments merging into what sounds distinctly like avian vocalizations.

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The project draws a fascinating parallel between this artificial acceleration and the natural world: birds, with their accelerated metabolism compared to humans, experience time at a faster rate. This leads to an intriguing hypothesis: could birdsong be understood as a compressed form of larger musical structures? And if so, is it possible to decompress birdsong using new technologies?

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This perspective becomes particularly meaningful in light of a historical detail: both Beethoven's student Carl Czerny and Bremen's Kapellmeister W.K. Müller independently claimed that the Fifth Symphony's main theme was inspired by forest birds' calls from Vienna's Prater park, where Beethoven frequently walked.

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The project thus creates a compelling circular narrative: from bird calls to symphony and back to bird-like temporal compression, while simultaneously commenting on our contemporary experience of accelerated time.
 

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The longer the musical piece, the higher the pitch of the sound subjected to compression to 59 seconds. Thus, Beethoven's Symphony No. 5, compressed by a factor of 33.5, was indeed identified by the AI as bird chirping. The next experiment was conducted with Beethoven's String Quartet No. 7 Opus 59 Razumovsky, compressed by a factor of 59. The AI identified the resulting compressed sound as mouse squeaking. Beethoven's Symphony No. 9 Opus 125, compressed by a factor of 73 to 59 seconds of sound, was identified by the AI as the buzzing of a mosquito swarm.