Efficient coding of natural signals


The efficient coding hypothesis predicts that perceptual systems are optimally adapted to natural signal statistics. Previous work provided statistics of speech signals for 8 languages based on Principal Components Analysis (PCA), arguing that 4 frequency channels would be sufficient to optimally represent clean speech signals for each of these 8 languages. Extending these data to cochlear implant simulations in english, it has been shown that 6 to 7 frequency bands would be sufficient to optimally represent vocoded speech.

However, research on music perception in cochlear implanted listeners sheds light on potential limits associated with these results. Performance observed on vocoded signal material in normal-hearing listeners as well as in CI users is systematically better for speech signals than for music. Our aim is to compare statistical properties of natural music signals with previous work on speech in order to evaluate their respective contributions to this theoretical proposal.


You may download the poster from our presentation at the SpIN 2022 workshop:

  • Crouzet, O., Duniec, A. & Delais-Roussarie E. (2022). Principal Components Analysis of amplitude envelopes from spectral channels: A preliminary comparison between music and speech. SpIN 2022 - Speech in Noise Workshop, 20th-21st June 2022, Groningen, NL (on-line). (Get the poster presentation)

This project is funded by the RFI-Ouest Industries Créatives (RFI-OIC, Région Pays de la Loire) & Nantes Université.