Generative audio refers to the creation of audio files from databases of audio clips. This technology differs from AI voices such as Apple's Siri or Amazon's Alexa, which use a collection of fragments that are stitched together on demand.

Audio curves

Generative audio works by using neural networks to learn the statistical properties of an audio source, then reproduces those properties.[1]

Implications

With this technology, a person's voice can be replicated to speak phrases that they may have never spoken. This could lead to a synthetic version of a public figure's voice being used against them.[2]

Technology

This method uses generative adversarial network (GAN), a deep machine learning technique where two machine learning models work against each other to create realistic audio.[3]

See also

References

  1. ↑ "Fake news: you ain't seen nothing yet". The Economist. July 2017. Retrieved 2017-07-01.
  2. ↑ Zotkin, D. N.; Shamma, S. A.; Ru, P.; Duraiswami, R.; Davis, L. S. (April 2003). "Pitch and timbre manipulations using cortical representation of sound". 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). Vol. 5. pp. V–517–20. doi:10.1109/ICASSP.2003.1200020. ISBN 978-0-7803-7663-2. S2CID 10372569.
  3. ↑ Mobin, Shariq (October 2016). "Voice Conversion using Convolutional Neural Networks". arXiv:1610.08927 [stat.ML].
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